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Salesforce Offers Free AI Training

Salesforce Offers Free AI Training

Salesforce has announced plans to broaden access to free AI training through its Trailhead online platform, aiming to equip 100,000 additional students with essential AI skills. With AI becoming a transformative technology that nearly every business is investing in, the demand for AI training is rapidly increasing. To meet this need, Salesforce is expanding its free AI training programs via Trailhead, which offers courses and certifications designed to enhance learners’ AI capabilities. These resources will be available until the end of 2025. At a time when employers need to upskill employees on artificial intelligence, Salesforce is at the ready. In support of this initiative, Salesforce will open new spaces at its San Francisco headquarters, including a pop-up AI Center for in-person training and a dedicated floor for employees to develop AI skills. This expansion represents a $50 million investment in workforce development, addressing the growing AI skills gap. Salesforce aims to help every Trailblazer become an “Agentblazer,” a term for those trained on Salesforce products, by reaching 100,000 more learners through these offerings. Recent expansions to the Trailhead platform include AI-specific courses on fundamentals, ethical AI use, and prompting. Since June 2023, over 2.6 million AI and data badges have been earned by employees, jobseekers, and learners, unlocking critical skills. “AI and agents are reshaping how people work, and it’s essential that everyone has the skills to thrive in this new landscape,” said Brian Millham, president and COO of Salesforce. Tectonic credits Salesforce for offering equal training opportunities for partners, consultants, job seekers, and users. 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

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Predictive Analytics

Predictive Analytics in Salesforce

Predictive Analytics in Salesforce: Enhancing Decision-Making with AI In an ever-changing business environment, companies seek tools to forecast trends and anticipate challenges, enabling them to remain competitive. Predictive analytics, powered by Salesforce’s AI capabilities, offers a cutting-edge solution for these needs. In this guide, we’ll explore how predictive analytics works and how Salesforce empowers businesses to make smarter, data-driven decisions. What is Predictive Analytics? Predictive analytics uses historical data, statistical modeling, and machine learning to forecast future outcomes. With the vast amount of data organizations generate—ranging from transaction logs to multimedia—unifying this information can be challenging due to data silos. These silos hinder the development of accurate predictive models and limit Salesforce’s ability to deliver actionable insights. The result? Missed opportunities, inefficiencies, and impersonal customer experiences. When organizations implement proper integrations and data management practices, predictive analytics can harness this data to uncover patterns and predict future events. Techniques such as logistic regression, linear regression, neural networks, and decision trees help businesses gain actionable insights that enhance planning and decision-making. Einstein Prediction Builder A key component of the Salesforce Einstein Suite, Einstein Prediction Builder enables users to create custom AI models with minimal coding or data science expertise. Using in-house data, businesses can anticipate trends, forecast customer behavior, and predict outcomes with tailored precision. Key Features of Einstein Prediction Builder Note: Einstein Prediction Builder requires an Enterprise or Unlimited Edition subscription to access. Predictive Model Types in Salesforce Salesforce employs various predictive models tailored to specific needs: Building Custom Predictions Salesforce supports custom predictions tailored to unique business needs, such as forecasting regional sales or calculating appointment attendance rates. Tips for Building Predictions Prescriptive Analytics: Turning Predictions into Actions Predictive insights are only as valuable as the actions they inspire. Einstein Next Best Action bridges this gap by providing context-specific recommendations based on predictions. How Einstein Next Best Action Works Data Quality: The Foundation of Accurate Predictions The effectiveness of predictive analytics depends on the quality of your data. Poor data—whether due to errors, duplicates, or inconsistencies—can skew results and undermine trust. Best Practices for Data Quality Modern tools like DataGroomr can automate data validation and cleaning, ensuring that predictions are based on trustworthy information. Empowering Smarter Decisions with Predictive Analytics Salesforce’s AI-driven predictive analytics transforms decision-making by providing actionable insights from historical data. Businesses can anticipate trends, improve operational efficiency, and deliver personalized customer experiences. As predictive analytics continues to evolve, companies leveraging these tools will gain a competitive edge in an increasingly dynamic marketplace. Embrace the power of predictive analytics in Salesforce to make faster, more strategic decisions and drive sustained success. 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

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Salesforce and Microsoft

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

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Salesforce ERP Integration

Salesforce ERP Integration

Unlock the Power of Salesforce and ERP Integration Salesforce is known worldwide for its unmatched capabilities as a CRM platform. But when integrated with an ERP system, the potential multiplies. Together, they create a cohesive environment where workflows are streamlined, financial processes are optimized, decision-making is enhanced, and customer relationships are improved—all within one unified system. However, you might have questions like: How does ERP integration with Salesforce work? or What are the benefits of this integration? Let’s jump in and answer all your questions! What is ERP and Its Benefits? ERP (Enterprise Resource Planning) is software that integrates multiple business functions into a single platform. It enables you to manage key processes like human resources, accounting, sales, inventory, compliance, and order management. What makes ERP systems unique is the shared database that gives all employees access to the same real-time information across departments. While different from a CRM platform, ERP can be integrated with Salesforce to further boost business efficiency and productivity. Key benefits of an ERP system include: How Do Salesforce and ERP Work Together? Salesforce focuses on managing customer relationships, sales, marketing, and service operations. In contrast, ERP systems handle core business processes like finance, human resources, and supply chain management. When Salesforce and ERP are integrated, they create a seamless data flow between both systems. This integration synchronizes key data, like transactions and customer information, providing unified visibility across departments. It enhances efficiency and delivers better customer experiences by offering personalized services. Why Integrate Your ERP with Salesforce? While Salesforce helps manage customer relationships, integrating it with an ERP system offers additional advantages: Types of Salesforce – ERP Integrations There are various ways to integrate Salesforce with an ERP, depending on your business needs: Choosing the Right ERP to Integrate with Salesforce Not sure which ERP system is right for your Salesforce integration? Consider the following factors: ERP Systems Compatible with Salesforce Salesforce’s flexibility allows it to integrate with most ERP systems, including Sage Intacct, Sage X3, Sage 300, Sage 100, Sage 50 US, and Acumatica, among others. This flexibility ensures you can find the right ERP for your business operations. Key Functionalities with Salesforce – ERP Integration Here are some essential features you can expect from Salesforce and ERP integration: Best Practices for Seamless Integration To ensure a smooth Salesforce and ERP integration, follow these best practices: Conclusion Integrating an ERP system with Salesforce CRM can transform your business by unlocking new levels of productivity, efficiency, and growth. As your integration partner, Tectonic offers expertise in Salesforce and third-party ERP systems. Ready to streamline your operations and boost performance? Contact us today to start your ERP-Salesforce integration journey! 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

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Employees Have Different Motivations

Employees Have Different Motivations

The workforce has undergone significant changes over the last two years. Today’s employees have different motivations, seeking more flexibility and purpose, while also expecting more from corporate leaders. Employees Have Different Motivations. Similarly, customers now demand high levels of personalization and exceptional experiences. How can C-suite executives keep up with these evolving expectations? Our research highlights emerging priorities for corporate leaders in these challenging times. In a recent webinar, we asked two Inc. 5000 CEOs about shifting priorities and the critical role of enhancing employee experiences to meet rising customer demands. The message was clear: efficient growth starts with your employees. Focusing on employee satisfaction, providing clear paths for growth, establishing strong values, and investing in the right tools are key drivers of success. However, for some leaders, old habits hinder progress. Today’s executives must not only be digitally proficient but also agile, with strong emotional intelligence to manage change and new relationships effectively. A prime example of this disconnect is seen in employee engagement. Salesforce’s recent report, The Experience Advantage, found that while 71% of C-suite executives believe their employees are engaged, only 51% of employees agree. Similarly, 70% of executives think their employees are happy, but only 44% of employees share that sentiment. How can companies enable their leaders to succeed in this era of heightened expectations? Let’s explore the top priorities for CEOs today. Top Priorities for Corporate Leaders In a world where CEOs are accountable to more stakeholders than ever, they must navigate an increasingly complex landscape. They’re expected to speak on social issues, advocate for sustainability, and ensure stability in times of rapid change. Adaptability is crucial for success. Here are some current top priorities for corporate leaders: At Salesforce, they’ve found success by operating with startup-style values—centering consumer trust, fostering constant innovation, and setting clear, simple goals. Marc Benioff’s V2MOM framework exemplifies this alignment in action. The New Skills Leaders Need After reviewing research and interviewing business leaders, several trends have emerged. The most successful executives today share the following traits: A 2021 IBM Institute for Business Value survey of 3,000 global CEOs revealed similar trends, highlighting purposeful agility and making technology a priority. The study found that 56% of CEOs emphasized the need for operational flexibility, and 61% were focused on empowering remote work. Key technologies driving results over the next few years include the Internet of Things (79%), cloud computing (74%), and AI (52%). A major shift on leader agendas is the growing focus on employee experience. As Salesforce’s chief growth evangelist, Tiffani Bova, noted, “Employees are now the most important stakeholder to long-term success.” Providing seamless, consumer-like experiences for employees is now essential for business growth. Our research also uncovered a key gap: 73% of C-suite executives don’t know how to use employee data to drive change. This disconnect between leadership perception and actual employee experience is undermining growth. Emotional Intelligence (EQ) Matters To close this gap, sharpening leaders’ emotional intelligence is essential. Last year, we conducted interviews with 10 CEOs across various sectors. Many revealed plans to replace C-suite team members with more digitally savvy and emotionally intelligent leaders better equipped to manage the modern workforce. Summit Leadership Partners’ 2020 research found that 80-90% of top-performing executives excelled because of their high EQ. In fact, EQ is twice as predictive of performance as technical skills or IQ. The Changing Role of Key Executives Who do CEOs rely on most? A decade ago, IBM’s Institute for Business Value found that 47% of CEOs considered the chief innovation officer critical. Today, only 4% of CEOs agree. The chief marketing officer and chief strategy officer roles have also seen significant declines in perceived importance. The positions that have gained prominence include the chief technology officer (CTO) and chief information officer (CIO), now ranked third in importance after the chief financial officer (CFO) and chief operating officer (COO). As Jeff McElfresh, COO of AT&T, observed, “Not all leaders are comfortable managing in a distributed model. We’ve got work to do to unlock the potential.” The rise in job titles related to the future of work—up 60% since the pandemic—reflects this shift, with hybrid work models becoming more common. Diversity Drives Innovation and Profitability Diversity in leadership has become essential for driving revenue and innovation. McKinsey’s 2020 report Diversity Wins found that companies with more gender-diverse executive teams were 25% more likely to achieve above-average profitability. Similarly, those with greater ethnic diversity outperformed their peers by 36%. Diverse management teams also deliver 19% higher revenues from innovation compared to less-diverse teams, according to research from BCG. As diversity becomes increasingly tied to executive compensation, companies must support a diverse leadership pipeline by developing inclusive talent strategies. Moving Forward To thrive in today’s business world, corporate leaders must plan for change, ensure all executives have both digital literacy and emotional intelligence, and redistribute power to drive success. The healthiest C-suites will include diverse leaders in key positions like COO, CFO, and CIO/CTO. Aligning the business around common goals—like those in Salesforce’s V2MOM framework—and eliminating barriers for employees are key to staying ahead. Innovation must remain a top priority. By investing in the right tools and connected platforms, companies can reduce costs and drive sustainable growth. Reach out to Tectonic for assistance in making the innovations that recognizes Employees Have Different Motivations. 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

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Benefits of AI in Banking

Benefits of AI in Banking

Artificial intelligence (AI) is rapidly gaining traction in the banking and finance sector, with generative AI (GenAI) emerging as a transformative force. Financial institutions are increasingly adopting AI technologies to automate processes, cut operational costs, and boost overall productivity, according to Sameer Gupta, North America Financial Services Organization Advanced Analytics Leader at EY. While traditional machine learning (ML) techniques are commonly used for fraud detection, loan approvals, and personalized marketing, banks are now advancing to incorporate more sophisticated technologies, including ML, natural language processing (NLP), and GenAI. Gupta notes that EY is observing a growing trend of banks using ML to enhance credit approvals, improve fraud detection, and refine marketing strategies, leading to greater efficiency and better decision-making. A recent survey by Gartner’s Jasleen Kaur Sindhu reveals that 58% of banking CIOs have either deployed or plan to deploy AI initiatives in 2024, with this number expected to rise to 77% by 2025. “This indicates not only the growing importance of AI but also its fundamental role in shaping how banks operate and deliver value to their customers,” Sindhu said. “AI is becoming essential to the success of banking institutions.” Here are five key benefits of AI applications in banking: Despite the benefits, concerns about AI in banking persist, particularly regarding data privacy, bias, and ethics. AI can inadvertently extract personal information and raise privacy issues. Regulatory challenges and the potential for AI systems to perpetuate biases are also major concerns. As AI technology evolves, banks are investing in robust governance frameworks, continuous monitoring, and adherence to ethical standards to address these risks. Looking ahead, AI is expected to revolutionize banking by delivering personalized services, enhancing customer interactions, and driving productivity. Deloitte forecasts that GenAI could boost productivity by up to 35% in the top 14 global investment banks, generating significant additional revenue per employee by 2026. 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 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 Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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Salesforce Data Cloud and Zero Copy

Salesforce Data Cloud and Zero Copy

As organizations across industries gather increasing amounts of data from diverse sources, they face the challenge of making that data actionable and deriving real-time insights. With Salesforce Data Cloud and zero copy architecture, organizations can streamline access to data and build dynamic, real-time dashboards that drive value while embedding contextual insights into everyday workflows. A session during Dreamforce 2024 with Joanna McNurlen, Principal Solution Engineer for Data Cloud at Salesforce, discussed how zero copy architecture facilitates the creation of dashboards and workflows that provide near-instant insights, enabling quick decision-making to enhance operational efficiency and competitive advantage. What is zero copy architecture?Traditionally, organizations had to replicate data from one system to another, such as copying CRM data into a data warehouse for analysis. This approach introduces latency, increases storage costs, and often results in inconsistencies between systems. Zero copy architecture eliminates the need for replication and provides a single source of truth for your data. It allows different systems to access data in its original location without duplication across platforms. Instead of using traditional extract, transform, and load (ETL) processes, systems like Salesforce Data Cloud can connect directly with external databases, such as Google Cloud BigQuery, Snowflake, Databricks, or Amazon Redshift, for real-time data access. Zero copy can also facilitate data sharing from within Salesforce to other systems. As Salesforce expands its zero copy partner network, opportunities to easily connect data from various sources will continue to grow. How does zero copy work?Zero copy employs virtual tables that act as blueprints for the data structure, enabling queries to be executed as if the data were local. Changes made in the data warehouse are instantly visible across all connected systems, ensuring users always work with the latest information. While developing dashboards, users can connect directly to the zero copy objects within Data Cloud to create visualizations and reports on top of them. Why is zero copy beneficial?Zero copy allows organizations to analyze data as it is generated, enabling faster responses, smarter decision-making, and enhanced customer experiences. This architecture reduces reliance on data transformation workflows and synchronizations within both Tableau and CRM Analytics, where organizations have historically encountered bottlenecks due to runtimes and platform limits. Various teams can benefit from the following capabilities: Unlocking real-time insights in Salesforce using zero copy architectureZero copy architecture and real-time data are transforming how organizations operate. By eliminating data duplication and providing real-time insights, the use of zero copy in Salesforce Data Cloud empowers organizations to work more efficiently, make informed decisions, and enhance customer experiences. Now is the perfect time to explore how Salesforce Data Cloud and zero copy can elevate your operations. Tectonic, a trusted Salesforce partner, can help you unlock the potential of your data and create new opportunities with the Salesforce platform. Connect with us today to get started. 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

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Salesforce Continues to Push the Boundaries of AI Innovation

Salesforce Continues to Push the Boundaries of AI Innovation

In a strategic move to enhance its AI capabilities, Salesforce has announced the acquisition of Zoomin, a leader in unstructured data management solutions. This acquisition, expected to finalize in the fourth quarter of Salesforce’s fiscal year 2025, aligns with the company’s mission to dominate the enterprise AI landscape through its Agentforce platform. The acquisition further highlights Salesforce’s commitment to advancing AI-driven customer experiences and operational efficiency. Financial details of the transaction were not disclosed, but Salesforce confirmed that it would not affect previous earnings guidance. Previously, in discussions around Service Cloud’s push for Unified Knowledge, there were concerns about relying on partners like Zoomin. This acquisition addresses those concerns by filling a critical gap in Salesforce’s product offerings and adding new functionalities to Data Cloud. Strengthening Data Cloud for AI Zoomin’s technology will enhance Salesforce’s Data Cloud by providing improved support for managing unstructured data—a cornerstone of modern AI systems. This is a critical step in Salesforce’s AI strategy, particularly for the Agentforce platform, as it enables more comprehensive, context-aware AI capabilities. Rahul Auradkar, Salesforce’s EVP & GM of Unified Data Services & Einstein, stressed the importance of this acquisition. “Unstructured data is the key to unlocking AI’s full potential in customer interactions,” Auradkar said. “With Zoomin’s technology, we’re not just improving data management—we’re revolutionizing how AI agents understand and use information to deliver personalized experiences.” The integration of Zoomin’s Unified Knowledge technology directly addresses a key challenge in AI: managing and understanding unstructured data to create smarter AI agents. By strengthening its data foundation, Salesforce is positioning itself to deliver more sophisticated AI applications across its platform. Agentforce: A New AI Frontier Salesforce’s recently launched Agentforce platform aims to revolutionize enterprise AI with autonomous AI agents capable of advanced decision-making and task automation. By incorporating Zoomin’s technology, Agentforce will gain the ability to process and utilize unstructured data more effectively, setting it apart from competitors like Microsoft’s Copilot, which often requires significant user input and prompt engineering. The enhanced Agentforce platform will deliver a host of benefits, from improved customer service automation to more accurate sales forecasting and personalized marketing campaigns. By tapping into unstructured data, Salesforce is paving the way for AI-driven insights and actions previously unattainable with traditional approaches. A Natural Progression from Partnership to Acquisition Zoomin’s relationship with Salesforce began in 2018 as an AppExchange partner, followed by an investment from Salesforce Ventures in 2019. This acquisition marks a natural progression in their partnership, promising a smooth integration into Salesforce’s ecosystem. Zoomin CEO Gal Oron shared his enthusiasm: “Joining forces with Salesforce is a natural next step for us. Our shared vision is to make AI truly intelligent by giving it access to the vast amount of unstructured data that exists in enterprises. Together, we’ll help businesses unlock the full potential of their data and AI investments.” Implications Across the Business Spectrum The integration of Zoomin’s technology is expected to have broad implications, especially in customer service, where AI agents can use unstructured data to deliver more personalized and efficient responses. Beyond customer service, this technology is poised to impact sales, marketing, and overall business operations, enabling deeper insights into customer behavior and more targeted campaigns. Kishan Chetan, EVP and GM of Salesforce Service Cloud, highlighted the potential: “With Unified Knowledge, we’re not just improving AI—we’re transforming how businesses understand and serve their customers. Imagine AI agents that can grasp the full context of a customer’s history, preferences, and needs in real time. That’s the power we’re unlocking.” A Strategic Response to the AI Arms Race Salesforce’s acquisition of Zoomin comes amid an increasingly competitive enterprise AI landscape. By bolstering its embedded AI capabilities through strategic acquisitions, Salesforce is solidifying its position as a leader in enterprise AI, while addressing key challenges faced by rivals like Microsoft and Google. Zoomin’s expertise in processing large volumes of technical content and generating insights based on user behavior will be instrumental in helping Salesforce deliver cutting-edge, AI-driven solutions. These advancements will improve everything from customer service to digital transformation initiatives across industries. With this acquisition, Salesforce continues to push the boundaries of AI innovation, cementing its leadership in the rapidly evolving enterprise AI market. 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

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Strawberry AI Models

Strawberry AI Models

Since OpenAI introduced its “Strawberry” AI models, something intriguing has unfolded. The o1-preview and o1-mini models have quickly gained attention for their superior step-by-step reasoning, offering a structured glimpse into problem-solving. However, behind this polished façade, a hidden layer of the AI’s mind remains off-limits—an area OpenAI is determined to keep out of reach. Unlike previous models, the o1 series conceals its raw thought processes. Users only see the refined, final answer, generated by a secondary AI, while the deeper, unfiltered reasoning is locked away. Naturally, this secrecy has only fueled curiosity. Hackers, researchers, and enthusiasts are already working to break through this barrier. Using jailbreak techniques and clever prompt manipulations, they are seeking to uncover the AI’s raw chain of thought, hoping to reveal what OpenAI has concealed. Rumors of partial breakthroughs have circulated, though nothing definitive has emerged. Meanwhile, OpenAI closely monitors these efforts, issuing warnings and threatening account bans to those who dig too deep. On platforms like X, users have reported receiving warnings merely for mentioning terms like “reasoning trace” in their interactions with the o1 models. Even casual inquiries into the AI’s thinking process seem to trigger OpenAI’s defenses. The company’s warnings are explicit: any attempt to expose the hidden reasoning violates their policies and could result in revoked access to the AI. Marco Figueroa, leader of Mozilla’s GenAI bug bounty program, publicly shared his experience after attempting to probe the model’s thought process through jailbreaks—he quickly found himself flagged by OpenAI. Now I’m on their ban list,” Figueroa revealed. So, why all the secrecy? OpenAI explained in a blog post titled Learning to Reason with LLMs that concealing the raw thought process allows for better monitoring of the AI’s decision-making without interfering with its cognitive flow. Revealing this raw data, they argue, could lead to unintended consequences, such as the model being misused to manipulate users or its internal workings being copied by competitors. OpenAI acknowledges that the raw reasoning process is valuable, and exposing it could give rivals an edge in training their own models. However, critics, such as independent AI researcher Simon Willison, have condemned this decision. Willison argues that concealing the model’s thought process is a blow to transparency. “As someone working with AI systems, I need to understand how my prompts are being processed,” he wrote. “Hiding this feels like a step backward.” Ultimately, OpenAI’s decision to keep the AI’s raw thought process hidden is about more than just user safety—it’s about control. By retaining access to these concealed layers, OpenAI maintains its lead in the competitive AI race. Yet, in doing so, they’ve sparked a hunt. Researchers, hackers, and enthusiasts continue to search for what remains hidden. And until that veil is lifted, the pursuit won’t stop. 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 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 Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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Data Governance for the AI Enterprise

Data Governance for the AI Enterprise

Salesforce Introduces Data Governance for the AI Enterprise Salesforce this month unveiled Data Governance for the AI Enterprise, a comprehensive suite of tools designed to help IT teams navigate the growing regulatory landscape surrounding generative AI. Why it matters: As governments worldwide work to implement stricter rules governing the use of AI, like the EU’s AI Act, data governance has become a top priority for businesses. According to Salesforce research, ensuring robust data security and governance is now the leading concern for Chief Data Officers. Cloud Data Security & Privacy SolutionsExplore the new suite: How Salesforce’s Data Governance for the AI Enterprise Can Help: Salesforce’s latest solution is designed to help companies proactively address both current and future regulations. Built on the Salesforce platform and integrated with Data Cloud, the suite offers advanced data management, enhanced security, and privacy features: Salesforce’s perspective:“Data governance is a top priority for every organization deploying AI, especially given the complexity of the regulatory landscape,” said Alice Steinglass, EVP and GM for Salesforce Platform. “Our Data Governance for the AI Enterprise suite equips businesses to tackle these challenges.” Customer success story:“Data encryption is essential to our data governance strategy,” said James Ferguson, Principal Security Architect at AWS. “With Salesforce’s flexible encryption solutions, we can maintain top-tier security while delivering innovative customer experiences.” Availability: For Data Cloud users: 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

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Integrate Digital Delivery and Human Connection

Integrate Digital Delivery and Human Connection

Salesforce’s latest data reveals a complex challenge for banks: while digital excellence is now essential for customer satisfaction, a fully digital experience risks alienating customers who value human connections at critical moments. Banks often feel torn between scaling digital capabilities and preserving the personal touch that fosters customer loyalty. How can they strike the right balance?

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Exploring Emerging LLM

Exploring Emerging LLM

Exploring Emerging LLM Agent Types and Architectures The Evolution Beyond ReAct AgentsThe shortcomings of first-generation ReAct agents have paved the way for a new era of LLM agents, bringing innovative architectures and possibilities. In 2024, agents have taken center stage in the AI landscape. Companies globally are developing chatbot agents, tools like MultiOn are bridging agents to external websites, and frameworks like LangGraph and LlamaIndex Workflows are helping developers build more structured, capable agents. However, despite their rising popularity within the AI community, agents are yet to see widespread adoption among consumers or enterprises. This leaves businesses wondering: How do we navigate these emerging frameworks and architectures? Which tools should we leverage for our next application? Having recently developed a sophisticated agent as a product copilot, we share key insights to guide you through the evolving agent ecosystem. What Are LLM-Based Agents? At their core, LLM-based agents are software systems designed to execute complex tasks by chaining together multiple processing steps, including LLM calls. These agents: The Rise and Fall of ReAct Agents ReAct (reason, act) agents marked the first wave of LLM-powered tools. Promising broad functionality through abstraction, they fell short due to their limited utility and overgeneralized design. These challenges spurred the emergence of second-generation agents, emphasizing structure and specificity. The Second Generation: Structured, Scalable Agents Modern agents are defined by smaller solution spaces, offering narrower but more reliable capabilities. Instead of open-ended design, these agents map out defined paths for actions, improving precision and performance. Key characteristics of second-gen agents include: Common Agent Architectures Agent Development Frameworks Several frameworks are now available to simplify and streamline agent development: While frameworks can impose best practices and tooling, they may introduce limitations for highly complex applications. Many developers still prefer code-driven solutions for greater control. Should You Build an Agent? Before investing in agent development, consider these criteria: If you answered “yes,” an agent may be a suitable choice. Challenges and Solutions in Agent Development Common Issues: Strategies to Address Challenges: Conclusion The generative AI landscape is brimming with new frameworks and fervent innovation. Before diving into development, evaluate your application needs and consider whether agent frameworks align with your objectives. By thoughtfully assessing the tools and architectures available, you can create agents that deliver measurable value while avoiding unnecessary complexity. 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

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Salesforce Einstein Copilot Security

Salesforce Einstein Copilot Security

Salesforce Einstein Copilot Security: How It Works and Key Risks to Mitigate for a Safe Rollout With the official rollout of Salesforce Einstein Copilot, this conversational AI assistant is set to transform how sales, marketing, and customer service teams interact with both customers and internal documentation. Einstein Copilot understands natural language queries, streamlining daily tasks such as answering questions, generating insights, and performing actions across Salesforce to boost productivity. Salesforce Einstein Copilot Security However, alongside the productivity gains, it’s essential to address potential risks and ensure a secure implementation. This Tectonic insight covers: Einstein Copilot Use Cases Einstein Copilot enables users to: All of these actions can be performed with simple, natural language prompts, improving efficiency and outcomes. How Einstein Copilot Works Here’s a simplified breakdown of how Einstein Copilot processes prompts: The Einstein Trust Layer Salesforce has built the Einstein Trust Layer to ensure customer data is secure. Customer data processed by Einstein Copilot is encrypted, and no data is retained on the backend. Sensitive data, such as PII (Personally Identifiable Information), PCI (Payment Card Information), and PHI (Protected Health Information), is masked to ensure privacy. Additionally, the Trust Layer reduces biased, toxic, and unethical outputs by leveraging toxic language detection. Importantly, Salesforce guarantees that customer data will not be used to train the AI models behind Einstein Copilot or be shared with third parties. The Shared Responsibility Model Salesforce’s security approach is based on a shared responsibility model: This collaborative model ensures a higher level of security and trust between Salesforce and its customers. Best Practices for Securing Einstein Copilot Rollout Prepare Your Salesforce Org for Einstein Copilot To ensure a smooth rollout, it’s critical to assess your Salesforce security posture and ready your data. Tools like Salesforce Shield can help organizations by: By following these steps, you can utilize the power of Einstein Copilot while ensuring the security and integrity of your data. 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

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Generative ai energy consumption

Growing Energy Consumption in Generative AI

Growing Energy Consumption in Generative AI, but ROI Impact Remains Unclear The rising energy costs associated with generative AI aren’t always central in enterprise financial considerations, yet experts suggest IT leaders should take note. Building a business case for generative AI involves both obvious and hidden expenses. Licensing fees for large language models (LLMs) and SaaS subscriptions are visible expenses, but less apparent costs include data preparation, cloud infrastructure upgrades, and managing organizational change. Growing Energy Consumption in Generative AI. One under-the-radar cost is the energy required by generative AI. Training LLMs demands vast computing power, and even routine AI tasks like answering user queries or generating images consume energy. These intensive processes require robust cooling systems in data centers, adding to energy use. While energy costs haven’t been a focus for GenAI adopters, growing awareness has prompted the International Energy Agency (IEA) to predict a doubling of data center electricity consumption by 2026, attributing much of the increase to AI. Goldman Sachs echoed these concerns, projecting data center power consumption to more than double by 2030. For now, generative AI’s anticipated benefits outweigh energy cost concerns for most enterprises, with hyperscalers like Google bearing the brunt of these costs. Google recently reported a 13% increase in greenhouse gas emissions, citing AI as a major contributor and suggesting that reducing emissions might become more challenging with AI’s continued growth. Growing Energy Consumption in Generative AI While not a barrier to adoption, energy costs play into generative AI’s long-term viability, noted Scott Likens, global AI engineering leader at PwC, emphasizing that “there’s energy being used — you don’t take it for granted.” Energy Costs and Enterprise Adoption Generative AI users might not see a line item for energy costs, yet these are embedded in fees. Ryan Gross of Caylent points out that the costs are mainly tied to model training and inferencing, with each model query, though individually minor, adding up over time. These expenses are often spread across the customer base, as companies pay for generative AI access through a licensing model. A PwC sustainability study showed that GenAI power costs, particularly from model training, are distributed among licensees. Token-based pricing for LLM usage also reflects inferencing costs, though these charges have decreased. Likens noted that the largest expenses still come from infrastructure and data management rather than energy. Potential Efficiency Gains Though energy isn’t a primary consideration, enterprises could reduce consumption indirectly through technological advancements. Newer, more cost-efficient models like OpenAI’s GPT-4o mini are 60% less expensive per token than prior versions, enabling organizations to deploy GenAI on a larger scale while keeping costs lower. Small, fine-tuned models can be used to address latency and lower energy consumption, part of a “multimodel” approach that can provide different accuracy and latency levels with varying energy demands. Agentic AI also offers opportunities for cost and energy savings. By breaking down tasks and routing them through specialized models, companies can minimize latency and reduce power usage. According to Likens, using agentic architecture could cut costs and consumption, particularly when tasks are routed to more efficient models. Rising Data Center Energy Needs While enterprises may feel shielded from direct energy costs, data centers bear the growing power demand. Cooling solutions are evolving, with liquid cooling systems becoming more prevalent for AI workloads. As data centers face the “AI growth cycle,” the demand for energy-efficient cooling solutions has fueled a resurgence in thermal management investment. Liquid cooling, being more efficient than air cooling, is gaining traction due to the power demands of AI and high-performance computing. IDTechEx projects that data center liquid cooling revenue could exceed $50 billion by 2035. Meanwhile, data centers are exploring nuclear power, with AWS, Google, and Microsoft among those considering nuclear energy as a sustainable solution to meet AI’s power demands. Future ROI Considerations While enterprises remain shielded from the full energy costs of generative AI, careful model selection and architectural choices could help curb consumption. PwC, for instance, factors in the “carbon impact” as part of its GenAI deployment strategy, recognizing that energy considerations are now a part of the generative AI value proposition. As organizations increasingly factor sustainability into their tech decisions, energy efficiency might soon play a larger role in generative AI ROI calculations. 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

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Salesforce AI Evolves with the Generative AI Landscape

Salesforce AI Evolves with the Generative AI Landscape

Salesforce AI: Powering Customer Relationship Management Salesforce is a leading CRM solution that has long delivered cutting-edge cloud technologies to manage customer relationships effectively. In recent months, the platform has further advanced with the integration of generative AI and AI-powered features, primarily through its AI engine, Einstein. Salesforce AI Evolves with the Generative AI Landscape. To explore how AI operates within the Salesforce ecosystem and how various business teams can leverage these innovations, this guide delves into Salesforce’s AI capabilities, products, and features. Salesforce AI: Transforming CRM Capabilities Salesforce remains a top choice in the CRM software market, offering one of the most comprehensive solutions for managing relationships across departments, industries, and initiatives. Through dedicated cloud platforms, Salesforce enables teams to oversee marketing, sales, customer service, e-commerce, and more, with tools focused on delivering enhanced customer experiences supported by powerful data analytics. With the introduction of generative AI, Salesforce has significantly elevated its native automation, workflow management, data analytics, and assistive capabilities for customer lifecycle management. Einstein Copilot exemplifies this innovation, aiding internal users with tasks such as outreach, analysis, and improving external user experiences. What is Salesforce Einstein? Salesforce Einstein is an AI-driven suite of tools integrated natively into various Salesforce Cloud applications, including Sales Cloud, Marketing Cloud, Service Cloud, and Commerce Cloud. It also operates through assistive technologies like Einstein Copilot. Einstein is built on a multitenant platform and incorporates numerous automated machine learning features to unify organizational data with CRM capabilities. Designed to make intelligent, data-driven decisions, Einstein requires no additional installation, offering a seamless user experience when paired with a compatible subscription plan. 7 Key Features of Salesforce Einstein 7 Applications of Salesforce Einstein Future Trends in Salesforce AI Bottom Line: Salesforce AI Evolves with the Generative AI Landscape Salesforce continues to enhance its AI-powered features, keeping pace with advancements in generative and predictive AI. Whether new to the platform or a seasoned user, Salesforce offers innovative, AI-centric solutions to streamline customer relationship management and business operations. 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

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