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09Oct

Enterprise AI

Enterprise AI: Revolutionizing Business Operations for a Competitive Edge Enterprise AI refers to the suite of advanced artificial intelligence technologies—such as machine learning, natural language processing (NLP), robotics, and computer vision—that organizations use to transform operations, enhance efficiency, and gain a competitive advantage. These technologies demand high-quality data, skilled expertise, and adaptability to rapid advancements. Businesses increasingly adopt enterprise AI because of its ability to automate critical processes, reduce costs, optimize operations, and enable data-driven decision-making. According to McKinsey’s 2024 report, 72% of organizations now integrate AI into their operations, a significant increase from 50% just six years ago. However, implementing AI presents challenges, such as employee mistrust, data biases, lack of explainability, and managing AI’s fast evolution. Successful adoption requires aligning AI initiatives with organizational goals, fostering data trust, and building internal expertise. This guide provides a strategic roadmap for embracing enterprise AI, covering foundational concepts, advanced use cases, and ways to navigate common pitfalls. Why AI Matters in the Enterprise Enterprise AI is a transformative force, similar to how the internet revolutionized global businesses. By integrating AI into their operations, organizations can achieve: AI-driven applications are reshaping industries by enabling hyper-personalized customer experiences, optimizing supply chains, and automating repetitive tasks to free employees for higher-value contributions. The rapid pace of AI innovation requires leaders to consistently re-evaluate its alignment with their strategies while maintaining effective data management and staying informed on evolving tools and regulations. AI’s Transformational Impact on Business AI’s potential is as groundbreaking as electrification in the 20th century. Its immediate influence lies in automating tasks and augmenting human workflows. For example: Generative AI tools like ChatGPT and Copilot further accelerate adoption by automating creative and intellectual tasks. Key Benefits of Enterprise AI Challenges of Enterprise AI Despite its benefits, AI adoption comes with hurdles: Ethical concerns, such as workforce displacement and societal impacts, also demand proactive strategies. AI and Big Data: A Symbiotic Relationship AI thrives on large, high-quality datasets, while big data analytics leverage AI to extract deeper insights. The rise of cloud computing amplifies this synergy, enabling scalable, cost-effective AI deployments. Evolving AI Use Cases AI continues to redefine industries, turning complex tasks into routine operations: Future AI Trends to Watch Building the Future with Responsible AI As AI advances, organizations must prioritize responsible AI practices, balancing innovation with ethical considerations. Developing robust frameworks for transparency and governance is essential to maintaining trust and fostering sustainable growth. AI’s future offers vast opportunities for businesses willing to adapt and innovate. By aligning AI initiatives with strategic goals and investing in robust ecosystems, enterprises can unlock new efficiencies, drive innovation, and lead in their industries. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 9, 2024in AI Tools, Artificial Intelligence, Data, Enterprise, Generative AI

08Oct

Veeam Latest Acquisition

Veeam continues its acquisition strategy with the purchase of Alcion, bolstering its capabilities in AI and as-a-service offerings. This acquisition follows Veeam’s investment in Microsoft 365 backup-as-a-service provider Alcion last year, and brings in a team of AI and security specialists. Analysts and Veeam executives see this move as a key step in expanding Veeam’s as-a-service offerings. Earlier this year, the company launched Veeam Data Cloud, a backup-as-a-service solution for Microsoft 365 and Azure workloads. “After years of resisting, Veeam has fully embraced the as-a-service model,” said Christophe Bertrand, an analyst at TheCube Research. Veeam Latest Acquisition The acquisition, which closed in mid-September, marks the second time Veeam has purchased a company founded by Niraj Tolia and Vaibhav Kamra. In 2020, Veeam acquired Kasten, their Kubernetes backup provider. A year ago, Veeam led a million funding round for Alcion, which has since developed AI-driven data protection solutions. Veeam has been active in acquisitions, joining a broader trend in the data protection market. Recently, Commvault acquired Clumio, Cohesity merged with Veritas, and Veeam itself bought Cirrus from CT4, which later became part of the Veeam Data Cloud. Earlier this year, Veeam also acquired Coveware, an incident response vendor. “Veeam hasn’t traditionally been an acquisition-heavy company, but that has changed in recent years,” said Rick Vanover, Veeam’s VP of product strategy. “I expect this trend to continue.” Alcion’s Role at Veeam This acquisition strengthens Veeam’s expertise in the fast-growing as-a-service market. Alcion’s team of fewer than 50 employees, including founders Niraj Tolia and Vaibhav Kamra, joins Veeam, with Tolia stepping in as Veeam’s new CTO. Tolia will lead product strategy and engineering for Veeam Data Cloud, succeeding Danny Allan, who recently became CTO at cybersecurity company Snyk. Alcion, which has hundreds of customers, will offer those customers the opportunity to transition to Veeam Data Cloud. However, Veeam has not finalized the future of Alcion’s product or established a timeline for its integration. “This acquisition brings incredible talent and thought leadership to Veeam, especially from Niraj and the Alcion team,” said Brandt Urban, Veeam’s senior VP of worldwide cloud sales. “Their expertise will help us rapidly enhance Veeam Data Cloud, adding more capabilities and expanding workload coverage.” Analysts, like Bertrand, expect Veeam to broaden its data protection offerings for additional SaaS platforms beyond Microsoft 365, looking toward collaboration and DevOps tools as potential areas for growth. AI and Security at the Forefront Alcion’s AI-powered features allow administrators to optimize backups, detect malware, and respond proactively to threats. According to Krista Case, an analyst at The Futurum Group, Alcion uses AI strategically to adapt backup schedules based on data modification patterns, trigger backups when potential threats are identified, and recommend the best recovery points. “When practitioners talk about cyber resilience, they’re focused on minimizing data loss and downtime—Alcion’s AI capabilities directly address these concerns,” said Case. Veeam has also been integrating AI into its existing products, offering inline malware detection and an Intelligent Diagnostics service. A forthcoming Copilot feature for Microsoft 365 backups will further enhance AI-driven data protection. Veeam Latest Acquisition “AI is a real asset when applied thoughtfully—it’s not just hype,” said Bertrand, adding that users are more interested in AI’s ability to drive outcomes, like detecting threats that could otherwise go unnoticed. Veeam executives echoed the importance of delivering clear, tangible AI benefits. “We keep user outcomes front and center because, otherwise, AI becomes an expensive experiment,” Vanover said. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 8, 2024in Data

08Oct

Data Cloud Model

While many Salesforce products like Sales Cloud, Service Cloud, Education Cloud, Health Cloud, and various industry clouds are built on a common ‘core’ platform that shares the same datastore (an Oracle relational database), Salesforce Data Cloud operates on (Data Cloud Model) a distinct architecture and technology stack. This insight explores the data models and related concepts that underpin the platform. Data Cloud Architecture and Storage Starting with the storage layer, Salesforce Data Cloud integrates multiple services: This combination enables Data Cloud to provide a petabyte-scale data store, overcoming the scalability and performance constraints of traditional relational databases. The physical architecture of Data Cloud is represented as a set of data objects, which form the foundation for how data is ingested, harmonized, and activated within the platform. Key Data Cloud Objects Data Source A Data Source is the initial data layer in Data Cloud, representing an external platform or system from which your data originates. Data Sources can include: Data Stream A Data Stream is an entity extracted from a Data Source, such as ‘Orders’ from Commerce Cloud, ‘Contacts’ from Sales Cloud, or ‘Subscribers’ from Marketing Cloud. Once a Data Source is connected to Data Cloud, Data Streams provide access to these entities and require assignment to a category: Profile, Engagement, or Other. A single Data Source can contain multiple Data Streams. Data Source Object (DSO) Data Streams are ingested into Data Source Objects (DSOs), which serve as temporary staging stores containing data in its raw, native format (e.g., CSV files). Minor transformations can be applied to fields during data ingestion. Data Lake Object (DLO) The next step in the data flow is the Data Lake Object (DLO). DLOs are typed, schema-based, materialized views that reside in the data lake (Amazon S3) and are generally stored as Apache Parquet files. This format, along with Apache Iceberg’s abstraction layer, supports efficient data storage and retrieval. DLOs are the first objects available for inspection and preparation of data, including field mapping and additional transformations. Data Model Object (DMO) Unlike DSOs and DLOs, which use a physical data store, Data Model Objects (DMOs) provide a virtual, non-materialized view into the data lake. Queries against a DMO return results based on the current data snapshot in DLOs, without storing them. DMOs can aggregate attributes from different Data Streams, Calculated Insights, and other sources. DMOs inherit their category from the first DLO mapped to them, and only DLOs with the same category can be mapped to the DMO. Like Salesforce objects, DMOs offer a canonical data model with pre-defined attributes (standard objects), and you can also create custom DMOs (custom objects). DMOs can have one-to-one or many-to-one relationships with other DMOs. Currently, there are 89 standard DMOs in Data Cloud, and this number is growing to support more use cases. DMOs are organized into various subject areas, including: Data Spaces Data Spaces offer logical partitions, allowing data to be segregated between different brands, regions, or departments, without the need for multiple Data Cloud instances. They also align with a Software Development Lifecycle (SDLC), enabling you to stage and test Data Objects in separate environments without affecting production data. Data Sources, Data Streams, and DLOs can be shared across Data Spaces, while DMOs and other platform features are isolated based on user permissions. Final Thoughts With the drop in storage costs and advancements in technology, companies now have vast datasets at their disposal. Every customer interaction, whether it’s a purchase, an email open, or a web page view, can be captured and stored. When properly organized, this data allows businesses to understand customers better, predict their needs, personalize interactions, and much more. However, one of Salesforce’s challenges is that its original platform, built over 20 years ago, was designed for a different era and struggles with handling voluminous, “big” data. Salesforce Data Cloud addresses these limitations with a modern architecture that overcomes the constraints of relational databases. Data Cloud is poised to become the backbone of the Salesforce platform, supporting the data needs of customers and products for the next two decades. If you’re interested in learning how to implement and integrate Salesforce Data Cloud in your organization, following best practices, reach out today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 8, 2024in Data, Google, Salesforce, Salesforce Data Cloud, Snowflake, Technology, Unified Knowledge

08Oct

Revolution Customer Service with Agentforce

Agentforce stole the spotlight at Dreamforce, but it’s not just about replacing human workers. Equally significant for Service Cloud was the focus on how AI can be leveraged to make agents, dispatchers, and field service technicians more productive and proactive. Join a conversation to unpack the latest Sales Cloud innovations, with a spotlight on Agentforce for sales followed by a Q&A with Salesblazers. During the Dreamforce Service Cloud keynote, GM Kishan Chetan emphasized the dramatic shift over the past year, with AI moving from theoretical to practical applications. He challenged customer service leaders to embrace AI agents, highlighting that AI-driven solutions can transform customer service from delivering “good” benefits to achieving exponential growth. He noted that AI agents are capable of handling common customer requests like tech support, scheduling, and general inquiries, as well as more complex tasks such as de-escalation, billing inquiries, and even cross-selling and upselling. In practice, research by Valoir shows that most Service Cloud customers are still in the early stages of AI adoption, particularly with generative AI. While progress has accelerated recently, most companies are only seeing incremental gains in individual productivity rather than the exponential improvements highlighted at Dreamforce. To achieve those higher-level returns, customers must move beyond simple automation and summarization to AI-driven transformation, powered by Agentforce. Chetan and his team outlined four key steps to make this transition. “Agentforce represents the Third Wave of AI—advancing beyond copilots to a new era of highly accurate, low-hallucination intelligent agents that actively drive customer success. Unlike other platforms, Agentforce is a revolutionary and trusted solution that seamlessly integrates AI across every workflow, embedding itself deeply into the heart of the customer journey. This means anticipating needs, strengthening relationships, driving growth, and taking proactive action at every touchpoint,” said Marc Benioff, Chair and CEO, Salesforce. “While others require you to DIY your AI, Agentforce offers a fully tailored, enterprise-ready platform designed for immediate impact and scalability. With advanced security features, compliance with industry standards, and unmatched flexibility. Our vision is bold: to empower one billion agents with Agentforce by the end of 2025. This is what AI is meant to be.” In contrast to now-outdated copilots and chatbots that rely on human requests and strugglewith complex or multi-step tasks, Agentforce offers a new level of sophistication by operating autonomously, retrieving the right data on demand, building action plans for any task, and executing these plans without requiring human intervention. Like a self-driving car, Agentforce uses real-time data to adapt to changing conditions and operates independently within an organizations’ customized guardrails, ensuring every customer interaction is informed, relevant, and valuable. And when desired, Agentforce seamlessly hands off to human employees with a summary of the interaction, an overview of the customer’s details, and recommendations for what to do next. Deploy AI agents across channelsAgentforce Service Agent is more than a chatbot—it’s an autonomous AI agent capable of handling both simple and complex requests, understanding text, video, and audio. Customers were invited to build their own Service Agents during Dreamforce, and many took up the challenge. Service-related agents are a natural fit, as research shows Service Cloud customers are generally more prepared for AI adoption due to the volume and quality of customer data available in their CRM systems. Turn insights into actionLaunching in October 2024, Customer Experience Intelligence provides an omnichannel supervisor Wall Board that allows supervisors to monitor conversations in real time, complete with sentiment scores and organized metrics by topics and regions. Supervisors can then instruct Service Agent to dive into root causes, suggest proactive messaging, or even offer discounts. This development represents the next stage of Service Intelligence, combining Data Cloud, Tableau, and Einstein Conversation Mining to give supervisors real-time insights. It mirrors capabilities offered by traditional contact center vendors like Verint, which also blend interaction, sentiment, and other data in real time—highlighting the convergence of contact centers and Service Cloud service operations. Empower teams to become trusted advisorsSalesforce continues to navigate the delicate balance between digital and human agents, especially within Service Cloud. The key lies in the intelligent handoff of customer data when escalating from a digital agent to a human agent. Service Planner guides agents step-by-step through issue resolution, powered by Unified Knowledge. The demo also showcased how Service Agent can merge Commerce and Service by suggesting agents offer complimentary items from a customer’s shopping cart. Enable field teams to be proactiveSalesforce also announced improvements in field service, designed to help dispatchers and field service agents operate more proactively and efficiently. Agentforce for Dispatchers enhances the ability to address urgent appointments quickly. Asset Service Prediction leverages AI to forecast asset failures and upcoming service needs, while AI-generated prework briefs provide field techs with asset health scores and critical information before they arrive on site. Setting a clear roadmap for adopting Agentforce across these four areas is an essential step toward helping customers realize more than just incremental gains in their service operations. Equally important will be helping customers develop a data strategy that harnesses the power of Data Cloud and Salesforce’s partner ecosystem, enabling a truly data-driven service experience. Investments in capabilities like My Service Journeys will also be critical in guiding customers through the process of identifying which AI features will deliver the greatest returns for their specific needs. Agentforce leverages Salesforce’s generative AI, like Einstein GPT, to automate routine tasks, provide real-time insights, and offer personalized recommendations, enhancing efficiency and enabling agents to deliver exceptional customer experiences. Agentforce is not just another traditional chatbot; it is a next-generation, AI-powered solution that understands complex queries and acts autonomously to enhance operational efficiency. Unlike conventional chatbots, Agentforce is intelligent and adaptive, capable of managing a wide range of customer issues with precision. It offers 24/7 support, responds in a natural, human-like manner, and seamlessly escalates to human agents when needed and redefining customer service by delivering faster, smarter, and more effective support experiences. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM

October 8, 2024in Data, Enterprise, Generative AI, Salesforce, Unified Knowledge

07Oct

AI All Grown Up

If you thought Salesforce had fully embraced AI, think again. The company has much more in store. AI All Grown Up and Salesforce is the educator! Alongside the announcement of the new Agentforce platform, Salesforce has teased plans to offer free premium instructor-led courses and AI certifications throughout 2025, reflecting a bold commitment to fostering AI skills and expertise. We’ve talked quite a bit over the last year about the need for AI education, and lo and behold here comes Salesforce to the rescue! AI All Grown Up Ah, they grow up so fast. Once just a baby cradeled in our arms with endless possibilities and potential. It was just like a year or so ago we heard of ChatGPT. Prior to that most people’s main exposure to artificial intelligence was their smart phones, which today we realize weren’t reall that smart. Generative, predictive and agentic AI have barreled down the pipeline increasing our vocabulary, and understanding, of what artificial intelligence can do. From generative content to sounds and images, AI continued to amaze us. Then predictive AI did our calculations faster than we could have imagined. Then agentic AI did nearly everything imaginable. AI All Grown Up. Like a very proud mentor of the process, I want to talk about Salesforce’s major contribution. Addressing the AI Skills Gap: Salesforce’s $50 Million Investment As the veritable plethora of AI tools rapidly expands, Salesforce is taking proactive steps to address the growing AI skills gap by investing $50 million into workforce upskilling initiatives. The company aims to ensure that businesses and individuals are prepared to utilize their new wave of AI tools effectively. While the full details have yet to be released, Salesforce has revealed that its premium AI courses and certifications will be made available for free via Trailhead by the end of 2025. This could mean certifications such as AI Associate and AI Specialist, which currently cost $75 and $200 respectively, may soon be offered at no cost. Gratis. Free, Salesforce has also mentioned “premium instructor-led training,” sparking speculation that AI-focused, instructor-led Trailhead Academy courses could become accessible to everyone in the Salesforce ecosystem. Expanding AI Education with Global AI Centers Salesforce’s AI upskilling push is part of a broader initiative to establish “AI Centers” across the globe. Following the opening of its first center in London in June, Salesforce is planning to launch additional AI hubs in cities like Chicago, Tokyo, Sydney, and even a pop-up center in San Francisco. These centers will host in-person premium courses and serve as gathering spaces for industry experts, partners, and customers. This initiative benefits not only the Salesforce ecosystem by increasing AI knowledge where expertise is scarce, but also aligns with Salesforce’s strategy of bringing AI-driven solutions to market through new products like Copilot Studio, Data Cloud, and the newly launched Agentforce platform. Agentforce: Salesforce’s Third Wave of AI On August 28, 2024, Salesforce introduced Agentforce, a suite of autonomous AI agents that marks a significant leap in how businesses engage with customers. Described as the “Third Wave of AI,” Agentforce goes beyond traditional chatbots, providing intelligent agents capable of driving customer success with minimal human intervention. What is Agentforce? Agentforce is a comprehensive platform designed for organizations to build, customize, and deploy autonomous AI agents across various business functions, such as customer service, sales, marketing, and commerce. These agents operate independently, accessing data, crafting action plans, and executing tasks without needing constant human oversight. It is like Artificial Intelligence just graduated highschool and is off to a world of new adventures and growth opportunities at college or university! Key Features of Agentforce: The Technology Behind Agentforce At the core of Agentforce is the Atlas Reasoning Engine, a system designed to mimic human reasoning. Here’s how it works: Customization Tools: Agent Builder Agentforce provides tools like Agent Builder, a low-code platform for customizing out-of-the-box agents or creating new ones for specific business needs. With this tool, users can: The Agentforce Partner Network Salesforce’s partner ecosystem plays a key role in Agentforce’s versatility, with contributions from companies like AWS, Google, IBM, and Workday. Together, they’ve developed over 20 agent actions available through the Salesforce AppExchange. As proud parents we watch our Artificial Intelligence child venture into the world making friends along the way. Learning social skills. Benefits and Impact of Agentforce Early Adopters and Success Stories Several companies are already benefiting from Agentforce: Availability and Pricing of Salesforce’s AI All Grown Up Agentforce for Service and Sales will be generally available on October 25, 2024, with some components of the Atlas Reasoning Engine launching in February 2025. Pricing starts at $2 per conversation, with volume discounts available. The Future of AI and Work Salesforce’s ambitious vision is to empower one billion AI agents with Agentforce by the end of 2025. This reflects their belief that the future of work will involve a hybrid workforce, where humans and AI agents collaborate to drive customer success. AI All Grown Up and We Couldn’t Be Prouder Our amazing AI child has graduated college and ventured out into the workforce. Agentforce vs. Einstein Bots: What’s the Difference? Conclusion Agentforce represents a major leap forward in AI-powered customer engagement. By providing autonomous, intelligent agents capable of managing complex tasks, Salesforce is positioning itself at the forefront of AI innovation. As businesses continue to explore ways to improve efficiency and customer satisfaction, Agentforce could redefine how organizations interact with customers and streamline their operations. If this is the Third Wave of AI, what will the fourth wave bring? Written by Tectonic’s Solutions Architect, Shannan Hearne Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business

October 7, 2024in Agentforce Platform, AI Tools, Data, Google, Mulesoft, Salesforce, Technology

05Oct

AI Era Demands an Intelligent Data Infrastructure

Why the AI Era Demands an Intelligent Data Infrastructure NetApp aims to bridge the gap between cloud-based AI models and on-premises data management systems, addressing a major challenge many organizations face as they explore emerging AI capabilities, such as generative AI. AI Era Demands an Intelligent Data Infrastructure. While the most advanced AI tools often reside in hyperscale clouds, the key data of most organizations remains on-premises. As companies move from AI experimentation to scaling their initiatives, they face the complex task of closing the divide between their data and AI. At first glance, the solution seems simple: Organizations can integrate their proprietary data with cloud-based AI services to enhance large language models (LLMs) and other AI tools, leveraging their industry-specific expertise to generate unique insights and drive value. In fact, a recent Enterprise Strategy Group (ESG) survey found that 84% of respondents believed incorporating enterprise data was critical to supporting their generative AI efforts. However, achieving this at scale is far more difficult than it appears. Many organizations are reluctant to send their valuable data to public clouds due to concerns about security, such as exposing sensitive intellectual property or personal information. Additionally, managing the process of transferring large datasets, creating data copies, updating models with fresh data, and keeping track of everything over time adds cost and complexity. Beyond these logistical issues, many organizations struggle with a fundamental challenge: poor data management. Rapid data growth, fragmentation, and a lack of understanding of their own data forces business users and data scientists to spend excessive time “data wrangling”—the process of identifying, gathering, and preparing data for AI models. This inefficiency delays training and deploying models, pushing back the point of inference, which is the key to unlocking value from AI. Increased latency also raises the risk that inferencing is based on outdated data, leading to repeated cycles and further inefficiency. This challenge has made data management a critical obstacle in AI adoption. ESG research identified poor data quality as the top challenge organizations face when implementing AI. Inadequate data is rapidly becoming a roadblock that hampers AI initiatives across industries. To address these challenges, NetApp has shifted its focus toward building an “intelligent data infrastructure” for the AI era. At the company’s Insight 2024 conference, NetApp outlined a strategy to support AI success by bridging the gap between cloud-based AI models and on-premises data environments. The company’s vision includes simplifying, automating, and mitigating risks in the data management workflow needed to scale AI in the enterprise. NetApp’s approach includes innovations like a global metadata namespace and enhancements to its OnTap software, which enable exploration, classification, and management of data across the NetApp ecosystem. These capabilities integrate directly into AI data pipelines, enabling scalable searches and retrieval-augmented generation inferencing. Additionally, NetApp’s new “disaggregated” storage architecture will support more cost-effective scaling for compute-heavy AI tasks such as model training. NetApp’s strategy also extends to the public cloud, where it already has strong partnerships with all three hyperscalers, offering NetApp services as first-party options in their clouds. The company is expanding this by developing additional cloud-native capabilities for AI, such as integrating Azure NetApp Files with Microsoft Azure AI services, FSx for NetApp OnTap with Amazon Bedrock, and Google Cloud NetApp Volumes with Google Vertex AI and BigQuery. These integrations will allow organizations to securely enrich public cloud-based AI models with their on-premises data, creating a scalable and secure environment for AI development. While some aspects of NetApp’s strategy will be delivered over the next year, many cloud integrations will be available sooner. NetApp is also building a partner ecosystem, including hardware partners like Lenovo and Nvidia, software ISVs, and service providers like Domino Data Labs, in addition to its cloud alliances. With this vision for intelligent data infrastructure, NetApp is positioning itself as a key enabler of AI-driven innovation, and it will be intriguing to watch how this strategy unfolds in the coming months. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 5, 2024in AI Tools, Data, Enterprise, Generative AI, Google

04Oct

Navigate the Competitive Landscape of Retail

A shorter shopping season, the rise of Chinese shopping apps, and value-conscious consumers are expected to result in modest growth this holiday season. According to Salesforce’s 2024 holiday shopping forecast, U.S. holiday sales (Nov. 1 – Dec. 31) are projected to grow 2% year-over-year, reaching $277 billion. Global sales are also predicted to increase by 2%, totaling .19 trillion. This reflects softer growth compared to 2023, when global holiday sales rose by 3%. Challenges Ahead Salesforce warns that the 2024 holiday season may be difficult for retailers, with consumers having less spending power, a shortened 26-day shopping window between Thanksgiving and Christmas, and 43% of shoppers carrying more debt than last year. Additionally, 47% of surveyed shoppers plan to spend the same as in 2023, while 40% intend to spend less. New data from Salesforce’s Shopping Index shows that two-thirds of global consumers say price will dictate their shopping choices, while less than a third will prioritize product quality. Impact of Chinese Shopping Apps Salesforce predicts that 21% of holiday purchases will come from Chinese apps like Temu, Shein, AliExpress, and TikTok, with 35% of consumers reporting increased use of these apps. TikTok, in particular, saw a 24% increase in purchases since April 2024, highlighting the growing influence of Chinese platforms on holiday shopping. Retail Strategies To navigate the competitive landscape, Salesforce recommends retailers use strategic discounts and AI-powered tools to improve efficiency, enhance customer relationships, and boost profit margins. “This season will be competitive and focused on pricing strategies,” said Caila Schwartz, Salesforce’s director of strategy and consumer insights. “Leveraging AI and customer data is essential to guide marketing campaigns and holiday promotions.” Key Findings Salesforce’s insights are based on data from 1.5 billion global shoppers across 64 countries, focusing on 12 key markets, including the U.S., Canada, and U.K. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 4, 2024in Data, Salesforce, Salesforce Commerce Cloud, Salesforce Marketing Automation, Salesforce Sales Cloud

03Oct

Agentforce Unveiled

Salesforce Unveils ‘Agentforce’ to Empower a Billion AI Agents by 2025 Salesforce has introduced Agentforce, a revolutionary suite of autonomous AI agents aimed at transforming service, sales, marketing, and commerce sectors. With Agentforce, companies can rapidly scale their operations, boost efficiency, and elevate customer satisfaction by leveraging intelligent agents that handle routine tasks and complex workflows. The Agentforce Atlas Reasoning Engine powers these agents, autonomously analyzing data, making decisions, and completing tasks. This engine enables organizations to easily build, customize, and deploy their own agents using intuitive low-code tools. In addition, the Agentforce Partner Network allows customers to integrate pre-built agents from industry leaders like AWS, Google, IBM, and Workday, offering even more flexibility. Real-world impact Companies like OpenTable, Saks, and Wiley are already deploying Agentforce within their existing systems to enhance workforce capabilities and scale operations. Agentforce works autonomously, retrieving the right data on demand, building action plans, and executing them without human intervention. However, when needed, it can seamlessly hand off tasks to human employees, providing an overview of interactions, customer details, and suggested next steps. For example, Wiley has reported a 40% increase in case resolution after implementing Agentforce to handle routine inquiries. During busy seasons, like back-to-school, Agentforce has helped Wiley streamline operations, freeing up employees to handle more complex cases. Saks is also leveraging Agentforce to elevate its personalized customer experiences, empowering employees with real-time insights to deliver exceptional service. A new era of AI-driven customer success Salesforce CEO Marc Benioff is confident that Agentforce represents the third wave of AI, surpassing traditional chatbots and copilots with its fully autonomous capabilities. “Agentforce is a revolutionary and trusted solution that seamlessly integrates AI across every workflow, embedding itself deeply into the heart of the customer journey. This means anticipating needs, strengthening relationships, driving growth, and taking proactive action at every touchpoint,” Benioff said. Unlike its predecessors, Agentforce operates independently, adapting to changing conditions using real-time data. Whether responding to a customer service inquiry, qualifying sales leads, or optimizing marketing campaigns, Agentforce makes timely, relevant decisions based on an organization’s custom settings. When more human oversight is required, the platform provides detailed summaries and recommendations to assist employees in making informed decisions. Agentforce’s scalability and future Salesforce’s ambitious goal is to empower one billion AI agents by the end of 2025. This bold vision stems from the understanding that 41% of employee time is often spent on repetitive, low-impact work, according to the Salesforce Trends in AI Report. By automating these tasks, Agentforce allows employees to focus on more strategic, high-value initiatives, creating a hybrid workforce that is more effective and adaptable. Benioff noted, “While others require you to DIY your AI, Agentforce offers a fully tailored, enterprise-ready platform designed for immediate impact and scalability. Our vision is bold, and this is what AI is meant to be.” As businesses worldwide continue to explore AI’s potential, Agentforce positions Salesforce as a leader in the next wave of AI innovation, where autonomous agents enhance every facet of business operations. With over 1,000 agents already active, the future of work is a dynamic blend of human expertise and AI-powered agents, enabling organizations to thrive in an increasingly competitive landscape. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 3, 2024in Einstein 1 Platform, Salesforce Einstein, Salesforce Optimization

03Oct

Marc Benioff Interviewed

Salesforce, now one of the most influential companies in tech history, was founded by Marc Benioff after his successful tenure at Oracle. Having witnessed the potential of the internet, Benioff realized it would usher in a new era for delivering enterprise software through the cloud. However, this new approach demanded a complete overhaul of traditional business models, marketing strategies, and software development practices. Salesforce would embody this transformation, evolving over the decades into a platform supporting a diverse array of enterprise applications. Today, Salesforce’s flagship initiative is Agentforce, a pioneering wave of AI agents built on the Salesforce platform. This initiative, which I covered in detail earlier this month, exemplifies Benioff’s forward-thinking vision for AI. He passionately argues that Salesforce is well-positioned to lead in this space, and his insights on AI and its potential are as compelling as they are thought-provoking. Before diving into Agentforce and Benioff’s views on AI, it’s important to explore his early life and the founding of Salesforce. Benioff’s path to becoming the CEO of one of the most powerful software companies in the world was shaped by an early interest in technology. His first foray into software development was creating an app called “How to Juggle,” which he sold for to CLOAD Magazine in Goleta, California. This early success marked the beginning of a long career in tech. Benioff went on to establish an Atari game company called Liberty Software and later wrote assembly code for the Mac as part of an internship. Despite his success as a software developer, he transitioned to a leadership role after realizing his interest in the broader business of technology. He credits his time at Oracle, where he learned the intricacies of sales, marketing, and customer communication, as critical to shaping his vision for Salesforce. Oracle, during Larry Ellison’s prime, was an ideal place to hone these business skills, which Benioff would later apply to revolutionize the enterprise software space. With this foundation, Benioff founded Salesforce, a company that has fundamentally changed the way businesses engage with technology. The company’s success lies not just in its cloud-based software, but in its ongoing evolution to address new challenges, including the AI-powered Agentforce initiative, which stands at the forefront of Salesforce’s future growth. Benioff’s journey, from a young programmer to the CEO of a global tech giant, is a testament to his visionary approach and adaptability in an ever-changing tech landscape. Marc Benioff’s early entrepreneurial instincts were evident even before he fully embraced the title of entrepreneur. From a young age, he knew he wanted to build something of his own, though he hadn’t yet honed the full set of skills needed to succeed in business. He had a knack for technology, excelling as a programmer working in assembly code, but his mentors, including university professors and colleagues at Apple, recognized that being an entrepreneur required more than just technical ability. They encouraged him to develop his sales, marketing, and business acumen. His early exposure to these lessons was pivotal in shaping his future trajectory. Benioff’s transition from a programmer to a business leader began when he sought advice from Bill Jost at Apple, who connected him with Gary Gibson, an Oracle executive. After a memorable and unexpected interview, Benioff joined Oracle, starting with a role answering calls at the company’s 800-number. He quickly moved into sales and marketing, eventually working directly with Larry Ellison, who would become a significant mentor over the next 13 years. Benioff’s success at Oracle set the stage for his eventual departure to start Salesforce in 1999. In the mid-1990s, while at Oracle, Benioff had an epiphany while using a web browser. The internet was transforming how software could be delivered, and Benioff saw the potential for a new business model based on cloud computing. At this time, Oracle was focused on the network computer—a vision Benioff did not fully share. After discussing his ideas with Larry Ellison and taking some time off for reflection and research, Benioff recognized that the world was on the cusp of a major shift in technology. He felt compelled to create something new that would leverage the internet, offering software over the web through a subscription model. During his time off, Benioff traveled to Hawaii, reflecting on the future of the tech industry and contemplating ideas. He also experimented with domain names, purchasing You.com and later gifting it to a friend who turned it into a search and AI company. Benioff returned to Larry Ellison to share his vision of a cloud-based business model and later found inspiration from spiritual gurus during a trip to India, who reminded him that success in business should also be grounded in positive values. Benioff’s experience led to the founding of Salesforce with its revolutionary 1-1-1 Model—dedicating 1% of equity, profit, and employee time to philanthropy. Salesforce also embraced emerging technologies such as social, mobile, and AI, and created a new business model through subscription-based services. This combination of technological innovation and a strong sense of social responsibility has set Salesforce apart, attracting both admiration and emulation from other companies. Benioff’s Career Benioff’s career is a testament to the power of surrounding oneself with great people, continuing to learn, and having a clear vision. His leadership at Salesforce has been guided by values he believes are crucial to the company’s success and its ability to make a positive impact on the world. His insights on the Innovator’s Dilemma, a concept popularized by Clayton Christensen, highlight the challenges companies face as they evolve with changing technologies. While Salesforce’s core principles remain intact, the company has continued to adapt to new technology paradigms, ensuring it remains at the forefront of innovation in the software industry. Marc Benioff (MB) recently shared his excitement about the future of AI and its potential to revolutionize business and technology. He explained that, from a business perspective, this is the most thrilling moment in his career. AI, according to him, will transform how enterprises operate, making them more cost-efficient,

October 3, 2024in Agentforce Platform, Data, Enterprise, Google, Hyperforce, Salesforce, Salesforce Data Cloud, Snowflake, Technology

03Oct

What Makes a True AI Agent

What Makes a True AI Agent? Rethinking the Pursuit of Autonomy Unpacking the Core Traits of AI Agents — And Why Foundations Matter More Than Buzzwords The tech industry is enamored with AI agents. From sales bots to autonomous systems, companies like Salesforce and HubSpot claim to offer groundbreaking AI agents. Yet, I’ve yet to encounter a truly autonomous, agentic experience built from LLMs. The market is awash with what I call “botshit,” and if the best Salesforce can do is improve slightly over a mediocre chatbot, that’s underwhelming. What Makes a True AI Agent? But here’s the critical question everyone is missing: even if we could build fully autonomous AI agents, how often would they be the best solution for users? To explore this, let’s consider travel planning through the lens of agents and assistants. This use case helps clarify what each trait of agentic behavior brings to the table and offers a framework for evaluating AI products beyond the hype. By the end of this piece, you’ll be able to decide whether AI autonomy is a worthwhile investment or a costly distraction. The Spectrum of Agentic Behavior: A Practical Framework There’s no consensus on what truly defines an AI “agent.” Instead of relying on a binary classification, I suggest adopting a spectrum framework with six key attributes from AI research. This approach is more useful in today’s landscape because: Using the example of a travel “agent,” we’ll explore how different implementations fall on this spectrum. Most real-world applications land somewhere between “basic” and “advanced” tiers across the six traits. This framework will help you make informed decisions about AI integration and communicate more effectively with both technical teams and end users. By the end, you’ll be equipped to: What Makes a True AI Agent The Building Blocks of Agentic Behavior 1. Perception The ability to sense and interpret its environment or relevant data streams. An agent with advanced perception could, for instance, notice your preference for destinations with excellent public transit and factor that into future recommendations. 2. Interactivity The ability to engage with its environment, users, and external systems. LLMs like ChatGPT have set a high bar for interactivity. However, most customer support bots struggle because they need to integrate company-specific data and backend systems, prioritizing accuracy over creativity. 3. Persistence The ability to store, maintain, and update long-term memories about users and interactions. True persistence requires systems that not only store data but also evolve with each interaction, much like how a human travel agent remembers your favorite seat on a plane. 4. Reactivity The ability to respond to changes in its environment in real time. For example, a reactive system could suggest alternative travel dates if hotel prices surge due to a local event. 5. Proactivity The ability to anticipate needs and offer relevant suggestions unprompted. True proactivity requires robust perception, persistence, and reactivity to offer timely, context-aware suggestions. 6. Autonomy The ability to operate independently and make decisions within defined parameters. Autonomy varies by the level of resource control, impact scope, and operational boundaries. For example: The more complex the task and the greater the impact of a mistake, the more safeguards and precision the system needs. Proactive Autonomy: A Future Frontier The next step is proactive autonomy — the ability to modify goals or parameters to achieve overarching objectives. While theoretically possible, this introduces new risks and complexities, bringing us closer to the scenarios seen in sci-fi, where AI systems operate beyond human control. Most companies are nowhere near this level, and prioritizing foundation work like perception and persistence is far more practical for today’s needs. Agents vs. Assistants: A Useful Distinction An AI agent demonstrates at least five of the six attributes and exhibits autonomy within its domain. An AI assistant excels in perception, interactivity, and persistence but lacks autonomy or proactivity. It primarily responds to human requests and relies on human oversight for decisions. While many AI systems today are labeled “agents,” most function more like assistants. A Roomba, for example, is closer to an agent, autonomously navigating and adapting within a predefined space. On the other hand, tools like GitHub Copilot serve as powerful assistants, enhancing user capabilities without making independent decisions. Foundations Before Flash: The Role of Data Despite all the AI buzz, few companies today have the data foundations to support meaningful agentic behavior. For instance, most customer interactions rely on nuanced, unwritten information that is hard to automate. Missing perception foundations and inadequate testing lead to the “botshit” plaguing the industry. The key is to focus on building strong foundations in perception, interactivity, and persistence before tackling full autonomy. Start with the Problem: Why User-Centric AI Wins Before chasing the dream of autonomous agents, companies should start by asking what users actually need. Many organizations would benefit more from developing reliable assistants rather than fully autonomous systems. Real user problems, like those solved by Waymo and Roomba, offer clear paths to valuable AI solutions. The Path Forward: Align Data, Systems, and User Needs When deciding where to invest in AI: By focusing on foundational pillars, companies can build AI systems that solve immediate problems, laying the groundwork for more advanced capabilities in the future. Whether you’re developing agents, assistants, or indispensable tools, aligning solutions with real user needs is the key to meaningful progress. Contact Tectonic for assistance answering the question What Makes a True AI Agent work for my business? Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has

October 3, 2024in Data, Salesforce

03Oct

Supercharged Sales and Service Excellence

When sales and service teams are seamlessly aligned, organizations can transform every service interaction into a powerful opportunity to drive revenue and build customer loyalty. By delivering contextual, personalized offers at the right time, businesses can turn each customer touchpoint into a chance to solve problems, create value, and enhance engagement. With the help of real-time data and AI, we move beyond treating customer interactions as isolated events. Instead, we focus on understanding the unique needs and preferences of each customer, whether they’re reaching out for support, visiting a store, or engaging online. Every touchpoint becomes an opportunity to deliver tailored solutions, strengthen loyalty, and increase revenue. These examples are just a glimpse of the solutions we help our clients deploy. With our deep expertise in AI implementation and industry-specific insights, Tectonic is ideally positioned to guide you through activating AI agents that build on your successes. Our extensive experience across diverse sectors enables us to identify the most impactful opportunities for AI, ensuring tailored solutions that align with your business strategy. Tectonic’s proven approach ensures AI agents are deployed efficiently and effectively, driving ROI and delivering measurable results. Agentforce: Open, Extensible, and Transformative Agentforce is designed to foster smooth interactions between agents created on the platform and external agents and applications. With integration into Salesforce Data Cloud, it enables real-time data access for better, faster decision-making. Tectonic can help facilitate this interconnectivity across various channels and platforms, ensuring seamless operations. In a society that prioritizes digital, artificial intelligence is changing sales and service tactics. Adopting AI agents is crucial for business leaders to keep ahead of the competition and develop more effective and efficient methods of customer and employee support. AI agents are not just upgrades—they are transformative forces that redefine what’s possible. They empower organizations to move from envisioning possibilities to realizing a future of enhanced sales performance, streamlined operations, and unmatched customer satisfaction, all powered by AI. Salesforce’s Agentforce: Scaling Your Workforce with Autonomous AI Agents Agentforce provides fully customizable autonomous AI agents that can integrate with enterprise data and take action across sales, service, marketing, and commerce. The Agent Builder allows users to create agents that automate any business process, in any industry, using existing Salesforce tools such as workflows, Apex code, and prompt templates. Leading companies like The Adecco Group, BACA Systems, OpenTable, Saks, and Wiley are already leveraging Agentforce Service Agents to deliver faster, more personalized customer responses while improving operational efficiency. Salesforce (NYSE: CRM), the world’s #1 AI CRM, has announced the general availability of Agentforce. This new platform layer enables businesses to create and deploy AI agents that autonomously take action across any business function. Unlike traditional chatbots and copilots, Agentforce agents possess advanced reasoning abilities to make decisions and take actions such as resolving customer issues, qualifying sales leads, and optimizing marketing efforts. These agents operate independently—triggered by changes in data, business rules, pre-built automations, or external signals from APIs. Agentforce includes out-of-the-box agents that can be easily customized and deployed with low-code or no-code tools, working around the clock across any channel. The first of these, the Agentforce Service Agent, outperforms traditional chatbots by handling a wide range of tasks—from simple to complex—using pre-built topics and actions for customer support. These agents are fully customizable to serve various industries, such as retail with order management or financial services with billing and payment support. “Agentforce is redefining business possibilities, ushering in an era of AI-driven abundance and limitless workforces that enhance every employee’s capabilities, strengthen customer relationships, and fuel unprecedented growth,” said Marc Benioff, Chair and CEO of Salesforce. “Built on Salesforce’s trusted, fully customizable platform—integrating enterprise data, metadata, AI models, workflows, security, and applications—Agentforce is everything AI was meant to be.” The Power of Agentforce With Agentforce, there’s no need for DIY AI. Unlike other platforms that require complex integrations and custom builds, Agentforce is natively built into the Salesforce Platform. Customers can instantly convert their existing Flows, prompt templates, Apex code, and APIs into agent actions, seamlessly connecting to enterprise data and security models. With the added power of native tools like Data Cloud, Slack, and MuleSoft, Agentforce offers a streamlined and efficient approach to scaling your workforce with AI. The new Agent Builder empowers Salesforce admins and developers to easily create AI agents with natural language instructions and guardrails, enabling even more customization and control. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 3, 2024in Agentforce Platform, Artificial Intelligence, Data, Enterprise, Google, Hyperforce, Mulesoft, Salesforce, Salesforce Data Cloud

02Oct

AI Agents and Work

With AI tools becoming increasingly prevalent in workplaces worldwide, the focus has shifted from their novelty to optimizing productivity and effectiveness. AI Agents and Work. At Dreamforce 2024, AI agents were a hot topic, particularly with the launch of Salesforce’s new Agentforce platform. However, Slack also made its mark in the AI space, keen to demonstrate its role in transforming the future of work. TechRadar Pro sat down with Slack CEO Denise Dresser to explore how AI is reshaping the platform and why businesses should embrace this transformation. “Work is Broken” “Work, fundamentally, is broken,” Dresser stated, explaining that many workers spend too much time on what she describes as “the work of work.” This often involves switching between disconnected enterprise apps and navigating through data silos just to access the basic information needed to perform their jobs. Dresser emphasized that AI is poised to relieve much of this burden. She highlighted the “incredible wave” of AI adoption across industries, with over 13,000 AI-powered apps built on Slack. “We’re really investing in ensuring AI works for every worker, driving more productivity,” she said, noting that we’re in one of the most significant periods of change in the workplace, full of both opportunity and questions. Slack’s AI-Powered Enhancements With the support of its parent company, Salesforce, Slack has fully embraced AI, offering a broad range of tools designed to improve productivity. Dresser pointed to Slack’s summarization tools, which streamline workflows by surfacing important items from channels and conversations—tools she finds invaluable in her own workday. In addition, Slack’s Huddles—quick, impromptu meetings—now come with AI enhancements, including a new canvas sidebar that generates summaries, notes, and action items in real-time from a live transcript. Slack AI is also integrated into Workflow Builder, allowing users to automate processes using natural language, eliminating the resistance that some workers may feel toward adopting AI. “Slack is the natural place for work,” Dresser said, explaining that the future of work will involve searching, collaborating, and taking action all within the flow of daily tasks. “That vision has never been more true, and never been more real, because this moment is here.” The Era of AI Agents AI agents represent another major step forward for Slack. Dresser noted that third-party integrations with tools like Adobe, Box, and Workday will help facilitate seamless conversations across multiple apps without the need to switch between them. “The era of agents is a big idea, and it’s happening now,” she remarked. However, Dresser stressed the importance of ensuring a smooth transition, noting that onboarding customers effectively will be key to fulfilling this vision. “We think that’s the future.” Looking Ahead: AI at the Core of Work With the technology now in place, the responsibility lies with workers and managers to leverage AI to enhance their daily routines. “What we focus on is making sure we build a product that people love,” Dresser said, adding, “there’s really no one in the world that can offer the breadth of product that can operate across your entire business at the scale we can.” Dresser concluded with optimism about the future of work: “We’re really excited about this innovation meeting this moment. I don’t think there could be a better time for us, and we’re very optimistic about what’s ahead.” Slack’s AI-powered future is designed to break down barriers, streamline workflows, and make work more efficient for everyone. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 2, 2024in Agentforce Platform, AI Tools, Data, Enterprise, Salesforce, Technology

01Oct

Salesforce Data Cloud Innovations Announced

Salesforce Data Cloud Drives Customer Experience Transformation with New Data and AI Innovations Salesforce has unveiled new innovations within its Data Cloud, enhancing the way organizations transform customer experiences by leveraging data and AI. Key advancements include expanded support for unstructured data, enabling native processing of audio and video content—such as webinars and calls—to unlock deeper insights into customer behavior. A standardized semantic data model ensures both Agentforce Agents and humans can consistently interpret and use data, while improved search capabilities enhance information discovery by factoring in customer context. Real-time data activations allow organizations to respond instantly to evolving customer needs, and new data security and governance features safeguard operations and prevent data exposure. “In this new era of AI and Agents, customer data and metadata are the new gold for the enterprise,” said Rahul Auradkar, EVP and GM for Data Cloud at Salesforce. “More companies are using Data Cloud to unify all their data—from customer interactions and product usage to IoT and social media data—gaining deeper insights across all touchpoints. Because Data Cloud is foundational to Salesforce, companies can act on this data to deliver personalized, meaningful customer experiences.” Data Cloud integrates with Salesforce Customer 360, Agentforce, Flow, and analytics, providing a trusted data foundation for personalized experiences and real-time analytics. It powers data-driven actions and workflows while securely enabling AI across all Salesforce applications. Leveraging zero-copy technology and MuleSoft connectors, Data Cloud can ingest data from hundreds of sources, including data lakes and warehouses. Integrated into the Salesforce Platform, this metadata seamlessly flows into Salesforce applications, governed by set policies. This gives every team a 360-degree customer view, driving AI, automation, and analytics without compromising security. Data Cloud also enhances Agentforce, providing contextual insights and guiding next-best steps, like automating follow-up emails or sharing detailed chat summaries with human agents. Tableau Semantics bridges the gap between AI and employees, ensuring they operate with consistent data definitions. The following new Data Cloud features will be available across various release stages: For more information, visit www.salesforce.com. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 1, 2024in Data, Enterprise, Mulesoft, Salesforce, Salesforce Data Cloud, Technology

01Oct

Data Governance in Salesforce

Use Case Highlights Introduction Salesforce is a powerful platform for building strong customer relationships. However, to maximize the value of your data, a strategic approach is essential. Unmanaged data can lead to inconsistencies, security vulnerabilities, and compliance issues, making it difficult to rely on Salesforce data for strategic decision-making. This data governance insight looks into data governance for Salesforce and highlights top tools that integrate seamlessly with the platform. While these tools are not exclusively built for Salesforce, they offer powerful features that enhance the accuracy, security, and regulatory compliance of your data. Implementing a data governance strategy with the right tools unlocks the hidden potential of your Salesforce data. Imagine making decisions based on reliable information, streamlining workflows, and maximizing data value—all possible with clean, trustworthy data at your fingertips. Disclaimer: The specific third-party security solutions mentioned in this insight are for informational purposes only and do not constitute endorsements by Tectonic. 6 Data Governance Tools for Salesforce Users Understanding the Importance of Data Governance in Salesforce Salesforce, a cornerstone for managing customer relationships, thrives on a rich data repository. However, unmanaged data growth can lead to inconsistencies, security vulnerabilities, and compliance hurdles, hindering the data’s potential to drive strategic decisions. Data governance goes beyond data management. It establishes principles and practices to ensure your Salesforce data is: Why is data governance crucial for Salesforce? Data governance transforms data from a potential liability into a strategic asset, driving informed decisions, fostering trust, and empowering your organization to achieve its goals. Key Challenges in Salesforce Data Governance Implementing robust data governance within Salesforce presents challenges: Evaluating Data Governance Tools for Salesforce Choosing the right data governance tool for Salesforce requires careful evaluation: Comparing Top Data Governance Solutions for Salesforce When comparing top data governance solutions, assess factors like features, pricing, scalability, and customer reviews. A comparison table can offer a quick overview of key features and differences between solutions. Product Key Features Pricing Collibra Centralized platform, business glossary management, data lineage tracking, access controls Starting at $170,000/year Dataedo Collaborative data catalog, data documentation, quality rules, improved data literacy Starting at $18,000/year Alation Data discovery and intelligence platform, searchable data catalog, business terms & data lineage Starting at $60,000/year OneTrust Data Governance AI-driven discovery & classification, integrated catalog, governance policy management Contact for pricing Talend Data Fabric Data quality checks, automated metadata management, data inventory & Trust Score, stewardship workflows Starting at $12,000/year Informatica Axon AI-powered discovery & quality assessment, stewardship communication, curated marketplaces, common dictionary Contact for pricing Data Governance in Salesforce This table provides a snapshot of key features and pricing, helping organizations make informed decisions based on their needs and budget. Reach out to Tectonic if you need assistance. Tectonic’s Remarks This insight has provided the knowledge to harness the true potential of your Salesforce data. Data governance is no longer a distant concept but a powerful practice that every organization must embrace. Success lies in selecting the right data governance solution. Consider your specific needs—whether it’s robust data lineage tracking offered by tools like Collibra and Talend, user-friendly interfaces from Dataedo and Alation, or cost-effectiveness. Several tools explored in this insight also offer strong security features to safeguard your customer data. Tools like Informatica Axon can assist with data discovery and quality assessment, empowering data stewards. By embracing data governance and leveraging the right tools, you can transform Salesforce data from a raw resource into a strategic asset. This newfound data clarity fuels informed decision-making, fosters customer trust, and drives your organization toward achieving its goals. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 1, 2024in Data, Enterprise, Salesforce

29Sep

Salesforce and Microsoft

Or is it Salesforce versus Microsoft? The Salesforce and Microsoft relationship is evolving. Or is it devolving? Earlier this year, Salesforce rebranded its Einstein Copilot to Agentforce. Following this change, co-founder and CEO Marc Benioff criticized Microsoft Copilot, comparing it to the outdated rules-based assistant “Clippy” from Microsoft Office in the 1990s and 2000s. Benioff’s critiques began on August 28 during the company’s latest quarterly earnings call, where he asserted that Microsoft customers have not seen value from their Copilot investments, referring to it as a “science project.” He reiterated his stance in his Dreamforce keynote, stating that Microsoft Copilot suffers from “a lack of context, skills, and adaptability.” This raises questions about Salesforce’s relationship with Microsoft. When directly asked, Benioff’s response was tinged with sarcasm: “Very good. I love them. They’re great. An impressive company.” He then recounted several of Microsoft’s historical competitive missteps, even referencing the U.S. government’s antitrust case against the company stemming from its battle with Netscape. Microsoft chose not to comment on this story. However, in response to Benioff’s criticisms following the late-August earnings call, Jared Spataro, Microsoft’s corporate vice president for artificial intelligence at work, highlighted that both internal and third-party metrics show a doubling of Copilot daily users in the previous quarter, along with a 60% increase in sales, indicating that Copilot adds value in the workplace. Salesforce reportedly serves about 150,000 customers, while Microsoft boasts an approximately 85% market penetration for productivity applications. This theoretically means that around 127,500 customers could integrate Microsoft 365 with Salesforce for email, calendar, tasks, and contact management. Salesforce claimed more than 25 million end users in 2022, suggesting that approximately 21.5 million users depend on collaboration between Salesforce and Microsoft for their systems to function effectively. “There’s always noise in the system,” said Ian Kahn, a principal at PwC and leader of the firm’s Salesforce practice. “Frankly speaking, I don’t think our clients care about it. You tune out the noise.” Rebecca Wettemann, founder of the research and advisory firm Valoir, noted that while she agrees with some of Benioff’s points—such as the underperformance of Copilots and limited customer deployment—many Salesforce customers are hosted on Microsoft’s Azure cloud. “You’ve got to play both sides,” Wettemann remarked. “You have to be on Azure because it’s one of the biggest public clouds, and people want to be there. But you also have to take potshots at Microsoft. That’s just how it works.” Salesforce’s AI tools are designed specifically for sales, service, marketing, and e-commerce, integrated within the company’s applications. Users can create agents in Slack, and there are many industry-specific tools tailored for different sectors. In contrast, Microsoft’s Copilots are more generalized and are embedded in various applications, featuring a no-code “wizard” interface to pull in data from multiple sources, including Salesforce. Microsoft recently added Copilot agents, AI assistants that automate and execute business processes. While there are similarities between Salesforce’s Agentforce and Microsoft’s Copilot, Benioff’s comparisons may not be entirely fair. Salesforce’s AI is more focused on service, sales, and marketing, whereas Microsoft targets productivity for office workers. That said, this kind of competitive banter is par for the course in the tech industry. As Wettemann pointed out, “If they didn’t make aggressive marketing claims, it wouldn’t be Dreamforce.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

September 29, 2024in AI Tools, Artificial Intelligence, Data, Salesforce

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