Einstein 1 Platform Archives - gettectonic.com - Page 3
21Jun

AI and Consumer Goods Cloud

Salesforce’s latest “rolling thunder” of AI enhancements brings significant innovations to Consumer Goods Cloud, leveraging the power of the Einstein AI platform already integrated into Sales Cloud and Service Cloud. These enhancements are designed to optimize planning and execution for consumer goods companies. Salesforce Consumer Goods Cloud is an industry-specific solution that helps consumer goods companies streamline their route-to-market processes. By unifying trade promotion management and retail execution capabilities on a single platform, it enables seamless collaboration between headquarters and field teams. Utilizing Salesforce’s core CRM functionality and the Einstein AI platform, Consumer Goods Cloud empowers companies with data-driven insights and intelligent automation to drive profitable growth. “Consumer goods companies are laser-focused on profitable growth. With the latest Salesforce innovations for Consumer Goods Cloud, they can unify consumer and customer data to plan promotions precisely, equip every field rep with tools to increase sales and reduce downtime, and integrate trusted AI into every service agent’s workflow to solve problems and upsell more frequently,” explained Rob Garf, VP and GM of Retail and Consumer Goods at Salesforce. “In short, every consumer goods company can now transform into an AI Enterprise.” What’s New in Consumer Goods Cloud The latest updates in Consumer Goods Cloud focus on integrating Salesforce’s Data Cloud with Einstein generative AI capabilities, enhancing three key areas: Data Cloud for Consumer Goods: Account managers can now unify account and industry data to build rich customer profiles, segment accounts to the individual store level, and design hyper-localized assortment and promotion plans. For instance, a soft drink distributor can identify which citrus-flavored sodas are most popular in specific Mexican convenience stores and optimize replenishment accordingly. Einstein Copilot Account Summarization: Within the service console, agents can access AI-generated account summaries, eliminating the need to switch between screens and knowledge articles. Summaries include last interactions, order history, satisfaction scores, and promotion details, enabling agents to resolve inquiries quickly and upsell intelligently. Consumer Goods Cloud Einstein 1 for Sales: This AI-powered enhancement package provides sales managers, field reps, merchandisers, and delivery drivers with productivity and revenue-boosting insights. Real-time notifications and recommendations on stock levels, replenishment, special handling needs, and payment collection keep field teams responsive and effective. The Salesforce Embedded AI Difference Salesforce’s strategy of embedding AI via a unified Einstein platform offers several advantages: Consistency: With Einstein already integrated into Sales and Service Clouds, Salesforce can efficiently extend proven AI tools to industry-specific use cases, benefiting users with familiar interfaces and interaction paradigms. Completeness: Embedding AI at the platform level allows Salesforce to enhance the entire workflow from planning to execution. Consumer goods companies can apply intelligent insights to both back-office processes like promotion management and field activities like stock checks and payment collection. Continuous Innovation: The Einstein platform enables rapid deployment of Salesforce’s latest generative AI advancements across all clouds, ensuring customers always have access to state-of-the-art capabilities. Mars Snacking, one of the world’s largest consumer goods companies, is already benefiting from Salesforce’s AI-powered industry cloud. “At Mars Snacking, we are on an ambitious journey to rewire and almost double the size of our business by 2030,” said Bartek Kononiuk, Global Head of Product – Trade Promotion Management. “Consumer Goods Cloud and Trade Promotion Management will enable us to improve our business processes, data availability, and user experience in critical growth-enabling areas.” AI Innovation Comes at a Cost As the consumer goods industry strives to meet rapidly evolving buyer expectations, Salesforce’s embedded AI solutions for Consumer Goods Cloud offer timely advantages. By democratizing access to generative AI and data management capabilities, Salesforce enables companies of all sizes to optimize decision-making, boost field productivity, and drive profitable growth. However, these advanced functionalities come with significant costs. Salesforce’s Einstein AI enhancements often have substantial per-user surcharges, sometimes exceeding $100 per month. For large deployments involving thousands of employees, these expenses can quickly escalate. Consumer goods companies must carefully evaluate the productivity and revenue gains against the added licensing costs. Additionally, while Salesforce is leading the way in enterprise generative AI, the technology is still maturing. Early adopters may encounter instances where the AI delivers suboptimal results. Salesforce’s Trust Layer aims to mitigate these risks, but companies should approach generative AI with a clear understanding of its current limitations. The ongoing enhancements in Salesforce’s Einstein portfolio present a promising yet costly opportunity for customers to evolve into full-fledged AI Enterprises. As the costs and benefits become clearer, consumer goods companies will need to strategically decide where and how aggressively to deploy these advanced capabilities. Those that find the right balance could gain a significant competitive edge in the rapidly changing digital 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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June 21, 2024in Einstein 1 Platform, Generative AI, Salesforce
Life Sciences Cloud Organizing Clinical Trials and Outreach
18Jun

Life Sciences Cloud Organizing Clinical Trials and Outreach

Salesforce CRM announced today its expansion into the life sciences sector with the launch of a new cloud platform designed to enhance engagement between medical technology providers, pharmaceutical companies, patients, and healthcare professionals. The Salesforce Life Sciences Cloud platform, now available, integrates advanced artificial intelligence capabilities from the Einstein 1 Platform. These AI capabilities aim to streamline clinical operations and processes by harnessing insights from all aspects of organizational data. Life Sciences Cloud Organizing Clinical Trials and Outreach. One of the primary benefits of the Life Sciences Cloud platform is its ability to optimize clinical trials, particularly in streamlining the recruitment and enrollment of participants. By leveraging AI, the platform can identify and match qualified candidates for clinical trials based on specific prescreening and eligibility criteria, significantly reducing the time traditionally spent on these processes. The platform facilitates the creation of personalized online portals for each clinical trial, making it easier for eligible patients to discover and enroll in trials relevant to them. It also simplifies the enrollment process through customizable e-consent forms. Using Einstein Copilot, an AI assistant, organizations can automate the identification of potential trial participants based on criteria such as proximity to trial sites, drawing data from sources like spreadsheets and electronic health records. This capability enhances efficiency by proactively reaching out to suitable candidates. Life Sciences Cloud Organizing Clinical Trials and Outreach Salesforce emphasizes the platform’s potential to alleviate common challenges in clinical trials, where recruitment delays and participant retention issues often hinder progress. By addressing these inefficiencies, Life Sciences Cloud aims to improve the operational timelines and success rates of clinical trials. Beyond clinical trials, the platform features a pilot patient benefits verification tool that helps organizations swiftly assess pharmaceutical costs and eligibility for financial assistance. Integrated with Einstein Copilot, this tool supports bulk re-verifications, ensuring continuous access to treatments for patients requiring periodic authorizations. Additionally, the platform includes a pilot patient program outcome management module, which automates the evaluation of educational and support programs’ impact on patients. This module aids in enhancing patient engagement and adherence to treatment plans by sending automated reminders and analyzing the effectiveness of engagement strategies. Salesforce’s Life Sciences Cloud also offers robust data analytics capabilities, leveraging Salesforce Data Cloud and MuleSoft for Life Sciences to unify structured and unstructured data sources. This unified data model provides comprehensive profiles for each patient and healthcare provider, enabling personalized interactions and informed decision-making. Frank Defesche, Senior Vice President and General Manager of Life Sciences at Salesforce, highlighted the platform’s role in enabling life sciences organizations to navigate challenges such as rising drug costs and regulatory complexities. He emphasized AI’s transformative potential in optimizing operational processes and prioritizing patient-centric approaches across the industry. Overall, Salesforce’s Life Sciences Cloud represents a significant advancement in leveraging AI-driven technologies to enhance efficiency, engagement, and outcomes within the life sciences sector. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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June 18, 2024in Einstein 1 Platform, Life Sciences Cloud, Mulesoft, Salesforce Data Cloud
Salesforce Driving Change
11Jun

Salesforce Driving Change

Sony Honda Mobility Leverages Salesforce Technology to Enhance Customer Relationships Sony Honda Mobility, a mobility tech startup, is utilizing Salesforce solutions—including Automotive Cloud, Data Cloud, Tableau, and MuleSoft—to deepen its customer relationships through enhanced data and insights. Sony Honda Mobility Inc. is a Japanese joint venture automotive company established by Sony Group Corporation and Honda Motor Company in 2022 to produce battery electric vehicles. The company will market its vehicles under the Afeela brand. Why It Matters: A significant 81% of business leaders report challenges with data fragmentation and silos. This disconnected, disjointed information often leads to immaterial and generic customer interactions, which is problematic as 80% of customers expect superior experiences given the extensive data companies collect. Key Developments: Sony Honda Mobility plans to launch its first electric vehicle in the United States in 2025, followed by Japan in 2026. To scale globally and stand out in the market, the company is empowering its service team with real-time data and insights on customer interactions with its products and services. How Is Salesforce Driving Change Data Cloud: A unified data platform that consolidates application, workflow, and data lake records, making it easier to train AI models, gain business insights, and improve customer relationships. Sony Honda Mobility is leveraging Data Cloud to integrate disparate data seamlessly across applications. MuleSoft API Integration: This integration connects data from Sony Honda Mobility’s vehicle and customer platform to Salesforce, ensuring a cohesive data flow. Automotive Cloud: Inside Automotive Cloud, Sony Honda Mobility now maintains a comprehensive profile of each customer and their vehicle, based on data from Data Cloud. This integration allows for personalized service and experiences at every touchpoint. The platform also streamlines contact center management, query handling, internal FAQ creation, web actions, and ongoing service support for incident and customer information management. Tableau: With Tableau’s visualizations of vehicle operation conditions and service usage status, Sony Honda Mobility can make quicker, more informed decisions about each customer’s needs. Customer Perspective “We aim to elevate our customer service and experiences to new heights. We are confident we can achieve this with Salesforce’s global expertise and proven track record in CRM, trusted AI, and data analytics,” said Yasuhide Mizuno, Chairman and CEO of Sony Honda Mobility. Salesforce Perspective “We are thrilled that Sony Honda Mobility has chosen the scalability, reliability, and expertise of Salesforce technology. By integrating their customer data on a single and trusted platform, we are excited to support Sony Honda Mobility as they scale excellent service to customers worldwide,” said Shinichi Koide, Chairman, President, and Chief Executive Officer of Salesforce Japan. The Result By harnessing Salesforce’s advanced technology, Sony Honda Mobility is poised to revolutionize its customer service and experience, ensuring a more connected, efficient, and personalized interaction for its customers globally. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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June 11, 2024in Einstein 1 Platform, Generative AI, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Implementation Services, Salesforce Manufacturing Automotive Energy, Salesforce Tableau
Democratize Data with Einstein Copilot for Tableau
10Jun

Democratize Data with Einstein Copilot for Tableau

Most workers today recognize the importance of rich data analytics in their jobs. However, 33% struggle to understand and generate insights from data. To address this, Salesforce has introduced Einstein Copilot for Tableau, which allows users of all skill levels to create complex data visualizations without extensive learning or coding. Democratize Data with Einstein Copilot for Tableau. Launched in April 2024, the beta version of this AI assistant features a user-friendly interface that simplifies the process with questions or simple commands. This facilitates the quick creation of comprehensive data presentations, including reports, dashboards, and various charts. Democratize Data with Einstein Copilot for Tableau Einstein Copilot for Tableau leverages a combination of AI technologies—natural language processing (NLP), machine learning (ML), and generative AI—to provide actionable insights. NLP enables conversational and intuitive interactions, while ML models process user queries and analyze data. Generative AI drives cognitive reasoning, planning, and creates insights, recommendations, and diagrams based on user inputs. By integrating with Tableau Cloud, Einstein Copilot accesses historical proprietary data, enables advanced data analysis, and translates user intent into actionable insights. It relies on Tableau’s analytics infrastructure to execute code and displays results through user-friendly visualizations and dashboards. Additionally, the Einstein Trust Layer secures and protects private data in Einstein Copilot. It authorizes inbound requests, ensuring users have necessary permissions to access specific data and safeguards model outputs to prevent the disclosure of confidential information. How Einstein Copilot for Tableau Transforms Requests into Insights To understand how Einstein Copilot for Tableau turns requests into actionable insights, let’s walk through each step of the interaction process: Einstein Copilot for Tableau democratizes access to data analytics, enabling all users to harness the power of data without needing extensive technical knowledge. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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June 10, 2024in Einstein 1 Platform, Salesforce Tableau
Salesforce Customers Take On AI Hallucinations
09Jun

Salesforce Customers Take On AI Hallucinations

Earlier this month, CRM specialists Salesforce hosted the latest edition of its World Tour Essentials event in Johannesburg. This event provided Salesforce with an opportunity to engage more personally with businesses in the region and showcase the AI-powered solutions it is developing, including the Einstein 1 platform. Now Salesforce Customers Take On AI Hallucinations. Einstein 1 is designed for AI-focused enterprises, leveraging existing CRM applications from Salesforce, along with data cloud and AI-powered tools. This platform aims to address key business challenges, one of which is the issue of generative AI hallucinations—where AI generates false information due to data gaps. A notable example of this issue was seen with Google’s Gemini, which produced bizarre and potentially harmful suggestions, like advising users to put epoxy glue on pizza. This occurred because the AI lacked sufficient data to generate accurate responses. While some companies continue to use the internet to train their platforms to avoid such hallucinations, businesses, particularly in the CRM field, cannot afford these inaccuracies. Salesforce has introduced a tool called Einstein 1 Studio to combat this problem. This tool allows business engineers and developers to create prompts and refine the overall experience of conversational platforms like Slack AI. During a media roundtable at the World Tour Essentials Johannesburg event, Linda Saunders, Salesforce’s Director of Solutions Engineering Africa, explained how Einstein 1 Studio helps mitigate AI hallucinations. “If you ask Einstein an ungrounded prompt like, ‘Please summarize the case for me,’ it may not know which case you’re referring to. By pulling metadata elements into the prompt and using certain word triggers, we can provide a much richer and more accurate AI response,” Saunders highlighted. She added that once a setup is built, it can be activated across multiple use cases, creating a consistent and efficient deployment process. Saunders also emphasized the importance of the trust layer within Einstein 1, which includes data grounding, audit trails, data masking, and mechanisms to prevent hallucinations. “The trust layer is integral to Einstein 1. Whether you build it or use the out-of-the-box capabilities, the trust layer ensures grounded data, audit trails, and other critical features,” Saunders explained. She also pointed out that Einstein 1’s building tools can address localization and tailor experiences to specific markets, like South Africa. “South African customers have unique needs compared to those in the US. This tool allows for prompt customization to better suit local business requirements,” Saunders noted. The configuration engine on top of Copilot functionality allows businesses to refine prompt engineering, ensuring that AI interactions are more tailored and effective. As AI integration becomes more widespread in business operations, addressing issues like AI hallucinations is crucial. According to Salesforce, Einstein 1 is designed with these considerations in mind, ensuring a reliable and accurate AI experience. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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June 9, 2024in Einstein 1 Platform, Generative AI
AI for Marketing and Retail
09Jun

AI for Marketing and Retail

Salesforce Expands AI Capabilities for Marketing and Retail with Einstein Copilot Salesforce is making waves in the marketing and retail sectors by enhancing its Einstein Copilot feature, bringing advanced AI tools even closer to its users. AI for Marketing and Retail. For those unfamiliar with Salesforce, it offers Einstein 1, a comprehensive platform integrating AI and machine learning across its various applications. Einstein Copilot, a part of this platform, functions as an AI-powered assistant designed to provide real-time assistance, automate tasks, and deliver contextual insights to boost productivity. New Additions: Einstein Copilot for Marketers and Merchants Salesforce has recently announced two exciting additions: Einstein Copilot for Marketers and Einstein Copilot for Merchants. Einstein Copilot for Marketers: Einstein Copilot for Merchants: Availability Einstein Copilot for Marketers is set to be generally available this summer, while Einstein Copilot for Merchants will enter the beta stage in the autumn. Leadership Insight “With the Einstein 1 Platform, we’re giving organizations the power to unify all of their data on one trusted platform,” said Ariel Kelman, President and CMO of Salesforce. “This is the key to getting results from generative AI that are actually useful in driving your business forward.” About Salesforce Founded in 1999, Salesforce is a cloud-based software company renowned as one of the best CRM software providers. With over 72,000 employees globally and an annual revenue of .49 billion, Salesforce continues to lead in innovation and customer satisfaction. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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June 9, 2024in Einstein 1 Platform, Generative AI
Gen AI Unleased With Vector Database
09Jun

Gen AI Unleased With Vector Database

Salesforce Unveils Data Cloud Vector Database with GenAI Integration Salesforce has officially launched its Data Cloud Vector Database, leveraging GenAI to rapidly process a company’s vast collection of PDFs, emails, transcripts, online reviews, and other unstructured data. Gen AI Unleased With Vector Database. Rahul Auradkar, Executive Vice President and General Manager of Salesforce Unified Data Services and Einstein Units, highlighted the efficiency gains in a one-on-one briefing with InformationWeek. Auradkar demonstrated the new capabilities through a live demo, showcasing the potential of the Data Cloud Vector Database. Enhanced Efficiency and Data Utilization The new Data Cloud integrates with the Einstein 1 platform, combining unstructured and structured data for rapid analysis by sales, marketing, and customer service teams. This integration significantly enhances the accuracy of Einstein Copilot, Salesforce’s enterprise conversational AI assistant. Gen AI Unleased With Vector Database Auradkar demonstrated how a customer service query could retrieve multiple relevant results within seconds. This process, which typically takes hours of manual effort, now leverages unstructured data, which makes up 90% of customer data, to deliver swift and accurate results. “This advancement allows our customers to harness the full potential of 90% of their enterprise data—unstructured data that has been underutilized or siloed—to drive use cases, AI, automation, and analytics experiences across both structured and unstructured data,” Auradkar explained. Comprehensive Data Management Using Salesforce’s Einstein 1 platform, Data Cloud enables users to ingest, store, unify, index, and perform semantic queries on unstructured data across all applications. This data encompasses diverse unstructured content from websites, social media platforms, and other sources, resulting in more accurate outcomes and insights. Auradkar emphasized, “This represents an order of magnitude improvement in productivity and customer satisfaction. For instance, a large shipping company with thousands of customer cases can now categorize and access necessary information far more efficiently.” Additional Announcements Salesforce also introduced several new AI and Data Cloud features: Auradkar noted that these innovations enhance Salesforce’s competitive edge by prioritizing flexibility and enabling customers to take control of their data. “We’ll continue on this journey,” Auradkar said. “Our future investments will focus on how this product evolves and scales. We’re building significant flexibility for our customers to use any model they choose, including any large language model.” For more insights and updates, visit Salesforce’s official announcements and stay tuned for further developments. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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June 9, 2024in Einstein 1 Platform, Hyperforce, Salesforce, Salesforce Einstein
Data Cloud Vector Database and Hyperforce
07Jun

Data Cloud Vector Database and Hyperforce

Salesforce World Tour Highlights: Data Cloud Vector Database and Hyperforce At the Salesforce World Tour on June 6, 2024, at the Excel Centre in east London, the focus was on advancements in the Data Cloud and Slack platforms. The event, sponsored by AWS, Cognizant, Deloitte, and PWC, showcased significant innovations, particularly for GenAI enthusiasts. Data Cloud Vector Database and Hyperforce. Vector Database in Data Cloud A key highlight was the announcement of the general availability of a Vector Database capability within the Data Cloud, integrated into the Einstein 1 Platform. This capability enhances Salesforce’s CRM platform, Customer 360, by combining structured and unstructured data about end-users. The Vector Database collects, ingests, and unifies data, allowing enterprises to deploy GenAI across all applications without needing to fine-tune an off-the-shelf large language model (LLM). Addressing Data Fragmentation Salesforce reports that approximately 80% of customer data is dispersed across various corporate departments in an unstructured format, trapped in PDFs, emails, chat conversations, and transcripts. The Vector Database unifies this fragmented data, creating a comprehensive profile of the customer journey. This unified approach not only improves customer engagement but also enhances organizational agility. By consolidating data from all corporate silos, companies can quickly and efficiently address issues such as product recalls and returns. Hyperforce: Enhancing Data Residency and Compliance During the keynote, Salesforce emphasized the importance of personalization in customer engagement and the benefits of deploying GenAI in customer-facing sectors. The event highlighted the need to overcome the fear and mistrust of GenAI and showcased how enterprises can enhance employee productivity through upskilling in GenAI technologies. One notable announcement was the general availability of Hyperforce, a solution designed to address data residency issues by integrating all Salesforce applications under the same compliance, security, privacy, and scalability standards. Built for the public cloud and composed of code rather than hardware, Hyperforce ensures safe delivery of applications worldwide, offering a common layer for deploying all application stacks and handling data compliance in a fragmented technology landscape. Salesforce AI Center The Salesforce AI Center was also introduced at the event. The first of its kind, located in the Blue Fin Building near Blackfriars, London, this center will support AI experts, Salesforce partners, and customers, facilitating training and upskilling programs. Set to open on June 18, 2024, the center aims to upskill 100,000 developers worldwide and is part of Salesforce’s $4 billion investment in the UK and Ireland. Industry Reactions and Future Prospects GlobalData senior analyst Beatriz Valle commented on Salesforce’s continued integration of GenAI across its portfolio, including platforms like Tableau, Einstein for analytics, and Slack for collaboration. According to Salesforce, the Data Cloud tool leverages all metadata in the Einstein 1 Platform, connecting unstructured and structured data, reducing the need for fine-tuning LLMs, and enhancing the accuracy of results delivered by Einstein Copilot, Salesforce’s conversational AI assistant. Vector databases, while not new, have gained prominence due to the GenAI revolution. They power the retrieval-augmented generation (RAG) technique, linking proprietary data with large language models like OpenAI’s GPT-4, enabling enterprises to generate more accurate results. Competitors such as Oracle, Amazon, Microsoft, and Google also offer vector databases, but Salesforce’s early investments in GenAI are proving fruitful with the launch of the Data Cloud Vector Database. Data Cloud Vector Database and Hyperforce Salesforce’s AI-powered integration solutions, highlighted during the World Tour, underscore the company’s commitment to advancing digital transformation. By leveraging GenAI and innovative tools like the Vector Database and Hyperforce, Salesforce is enabling enterprises to overcome the challenges of data fragmentation and compliance, paving the way for a more agile and competitive digital future. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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June 7, 2024in Einstein 1 Platform, Hyperforce, Salesforce, Salesforce Data Cloud
Consumer Chatbot Technology
07Jun

Consumer Chatbot Technology

The Reality Behind AI Chatbots and the Path to Autonomous AI In the rush to adopt the latest Consumer Chatbot Technology, it’s easy to overlook a fundamental reality: consumer chatbot technology isn’t ready for enterprise use—and it likely never will be. The reason is simple: AI assistants are only as effective as the data that powers them. Most large language models (LLMs) are trained on data from public websites, which lack the specific business and customer data that enterprises need. This means consumer bots can’t adequately assist employees in selling products, marketing merchandise, or improving productivity, as they lack the necessary personalization and business context. To achieve the vision of AI that goes beyond simple chatbots performing basic tasks—like drafting emails, essays, blogs, or graphics—to a more advanced role where AI acts autonomously and addresses business-critical needs, a different approach is needed. This vision involves AI taking action with minimal human intervention, using digital agents to identify and respond to these needs. At Salesforce, we are pursuing a clear path to AI that not only takes action but also automates routine tasks, all while adhering to established business rules, permissions, and context. Instead of relying solely on LLMs, which primarily focus on generating human-like text, future AI assistants will depend on large action models (LAMs) that integrate decision-making and action-taking capabilities. The Journey Toward AI Autonomy Our journey towards this vision began with the Salesforce Data Cloud, a robust data engine built on the Einstein 1 Platform. This platform integrates data from across the enterprise and third-party repositories, enabling companies to activate their data, automate workflows, personalize customer interactions, and develop smarter AI solutions. Recognizing the shift from generative AI to autonomous AI, Salesforce introduced Einstein Copilot, the industry’s first conversational, enterprise-class AI assistant. Integrated across the Salesforce ecosystem, Einstein Copilot utilizes an organization’s data, whether it’s behind a firewall or in an external data lake, to act as a reasoning engine. It interprets user intents, interacts with the most suitable AI model, solves problems, generates relevant content, and provides decision-making support. Expanding the Role of AI in Business Since its launch in February 2024, Salesforce has been expanding Einstein Copilot’s library of actions to meet specific business needs in sales, service, marketing, data analysis, and industries like ecommerce, financial services, healthcare, and education. These “actions” are akin to LEGO blocks—discrete tasks that can be assembled to achieve desired project outcomes. For example, a sales representative might use Einstein Copilot to generate a personalized close plan, gain insights into why a deal may not close, or review whether pricing was discussed in a recent call. Einstein Copilot then orchestrates these tasks, provides recommendations, and compiles everything into a detailed report. The ultimate goal is for AI not only to gather and organize information but also to take proactive action. Imagine a sales representative instructing their digital agent to set up meetings with top prospects in a specific territory. The AI could not only identify suitable contacts but also suggest meeting times, plan travel schedules, draft emails, and even create talking points—all of which it could execute autonomously with the representative’s approval. Tectonic dreams of the day AI is smart enough to interpret our search engine typos and produce the results for what we were actually looking for! The Future of AI Autonomy The possibilities for semi-autonomous or fully autonomous AI are vast. As we continue to develop and refine these technologies, the potential for AI to transform business processes and decision-making becomes increasingly tangible. At Salesforce, they are committed to leading this charge, ensuring that our AI solutions not only meet but exceed the expectations of enterprises worldwide. Salesforce is in a strong position to deliver on all of them because of the volume and breadth of data housed in Data Cloud, the heavy workflow traffic in our Customer 360 CRM, and the fact we’ve delivered an enterprise-class copilot that is rapidly expanding its library of actions. It will not happen overnight. The technology needs to advance, organizations and people have to be able to trust AI and be trained to use it in the right ways, and more work will need to be done to ensure the right balance between human involvement and AI autonomy. But with our continued investment in CRM, data, and trusted AI, we will achieve that vision before too long. Salesforce is in a strong position to deliver on all of them because of the volume and breadth of data housed in Data Cloud, the heavy workflow traffic in our Customer 360 CRM, and the fact we’ve delivered an enterprise-class copilot that is rapidly expanding its library of actions. Jayesh Govindarajan, Senior Vice President, Salesforce AI 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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June 7, 2024in Einstein 1 Platform, Generative AI, Salesforce Data Cloud
Trust Einstein Copilot for Tableau
04Jun

Trust Einstein Copilot for Tableau

Are you prepared to utilize the capabilities of Einstein Copilot to expand your organization’s analytical advantages? This robust tool facilitates data exploration, insights generation, and visualization development at an unprecedented pace. However, before immersing yourself in its capabilities, it’s crucial to grasp how Einstein Copilot upholds Tableau and Salesforce’s core value: Trust. Let’s discover how the Einstein Trust Layer safeguards your data, ensures result accuracy, and facilitates auditing, addressing common questions and concerns raised by our customers.Trust Einstein Copilot for Tableau. What is Einstein Copilot for Tableau? Using generative AI and statistical analysis, Einstein Copilot for Tableau is able to understand the context of your data to create and suggest relevant business questions to help kickstart your analysis. A smart, conversational assistant for Tableau users, Einstein Copilot for Tableau automates data curation—the organization and integration of data collected from various sources—by generating calculations and metadata descriptions. Einstein Copilot for Tableau can fill data gaps and enhance analysis by creating synthetic datasets where real data is limited. Einstein Copilot helps you anticipate outcomes with predictive analytics that simulate diverse scenarios and uncover hidden correlations. Additionally, generative models can increase data privacy by producing non-traceable data for analysis.  Fulfilling the promise of generative AI, Einstein Copilot for Tableau presents an efficient, insightful, and ethical approach to data analytics. Think of it as an intelligent assistant integrated into the Tableau suite of products to make everyone successful in their analysis workflow—whether they’re an experienced data analyst or a data explorer. As your intelligent analytics AI assistant, Einstein Copilot for Tableau guides you through the process of creating data visualizations in Tableau by assisting you with recommended questions, conversational data exploration, guided calculation creation, and more. Understanding the Einstein Trust Layer The Einstein Trust Layer constitutes a secure AI architecture embedded within the Salesforce platform. Comprising agreements, security technology, and data privacy controls, it ensures the safety of your data while exploring generative AI solutions. Built upon the Einstein Trust Layer, Einstein Copilot for Tableau and other Tableau AI features inherit its security, governance, and Trust capabilities. The Einstein Trust Layer is a secure AI architecture, built into the Salesforce platform. It is a set of agreements, security technology, and data and privacy controls used to keep your company safe while you explore generative AI solutions. Tableau has been on the journey to help people see and understand their data for over two decades. Thanks to data analysts, this mission has been a success and will continue to be a success. Data analysts are the backbone of organizations that champion data culture, capture business requirements, prep data, and create data content for end users. Data Access and Privacy Who Accesses Your Data? A primary concern among our customers revolves around data access. Rest assured, the Einstein Trust Layer enforces strict policies to safeguard your organization’s data. Third-party LLM providers, including Open AI and Azure Open AI, adhere to a zero data retention policy. This means that data sent to LLMs isn’t stored; once processed, both the prompt and response are promptly forgotten. Additionally, each Einstein Copilot for Tableau customer receives their own Data Cloud instance, securely storing prompts and responses for auditing purposes. Data Residency and Access Control Einstein Copilot for Tableau respects permissions, row-level security, and data policies within Tableau Cloud, ensuring that only authorized personnel within your organization access specific data. Whether using Einstein Copilot or not, data access is restricted based on organizational roles and permissions. Data Handling and Processing Data Sent Outside of Tableau Cloud Site Einstein Copilot for Tableau operates within the confines of your Tableau site, scanning connected data sources to create a summary context. This summarized data is sent to third-party LLM providers for vectorization, enabling accurate interpretation of user queries. Importantly, the zero data retention policy ensures that summarized data is forgotten post-vectorization. Personally Identifiable Information (PII) Data To enhance data privacy, Einstein Copilot for Tableau employs data masking for PII data. This technique replaces sensitive information with placeholder text, ensuring privacy without sacrificing context. While our detection models strive for accuracy, continuous evaluation and refinement are paramount to maintain trust. Result Trustworthiness Ensuring Safe and Accurate Results Einstein Copilot for Tableau employs Toxicity Confidence Scoring to identify harmful inputs and responses. By combining rule-based filters and AI models, potentially harmful content is filtered and flagged for review. Furthermore, accuracy benchmarks ensure that generated results align closely with human-authored ones, bolstering trust in the platform. Future Trust Enhancements Trust remains an ongoing focus for our teams. Initiatives such as a BYO LLM solution and improved disambiguation capabilities are underway to further enhance trustworthiness. Continuous feedback, testing, and iteration drive our efforts to maintain your trust in Einstein Copilot for Tableau and the Einstein Trust Layer. Data analysis and data-driven decision-making have been part of the vocabulary in organizations over the years. And, while data analysis is one of the most in-demand tech skills sought by employers today, not everyone in an organization has “analyst” in their job title—myself included. Yet, so many of us use data daily to make informed decisions. The rise of generative AI presents a significant opportunity for us to bring transformative benefits to analytics. Businesses are eager to embrace generative AI because it can help save time, provide faster insights, and empower analysts to be even more productive with an AI assistant—freeing analysts to focus on delivering high-quality, data-driven insights. Is Tableau replacing Einstein analytics? Einstein Analytics has a new name. Say hello to Tableau CRM. Everything about how it works stays the same, just with that snazzy new name. When Tableau joined the Salesforce family, we brought together analytics capabilities of incredible depth and power. What is the difference between Einstein analytics and Tableau? If you’re only planning on analyzing Salesforce data, Einstein Analytics would probably make the most sense for you. However, if you need to analyze information that is coming from all over the place, Tableau will give your users more options. Tableau GPT infuses automation in every part of analytics – from preparation to communicating

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June 4, 2024in Einstein 1 Platform, Salesforce Tableau
Einstein Personalization and Copilots
30May

Einstein Personalization and Copilots

Salesforce launched a suite of new generative AI products at Connections in Chicago, including new Einstein Copilots for marketers and merchants, and Einstein Personalization. Einstein Personalization and Copilots To gain insights into these products and Salesforce’s evolving architecture, Bobby Jania, CMO of Marketing Cloud was interviewed. Salesforce’s Evolving Architecture Salesforce has a knack for introducing new names for its platforms and products, sometimes causing confusion about whether something is entirely new or simply rebranded. Reporters sought clarification on the Einstein 1 platform and its relationship to Salesforce Data Cloud. “Data Cloud is built on the Einstein 1 platform,” Jania explained. “Einstein 1 encompasses the entire Salesforce platform, including products like Sales Cloud and Service Cloud, continuing the original multi-tenant cloud concept.” Data Cloud, developed natively on Einstein 1, was the first product built on Hyperforce, Salesforce’s new cloud infrastructure. “From the start, Data Cloud has been able to connect to and read anything within Sales Cloud, Service Cloud, etc. Additionally, it can now handle both structured and unstructured data.” This marks significant progress from a few years ago when Salesforce’s platform comprised various acquisitions (like ExactTarget) that didn’t seamlessly integrate. Previously, data had to be moved between products, often resulting in duplicates. Now, Data Cloud serves as the central repository, with applications like Tableau, Commerce Cloud, Service Cloud, and Marketing Cloud all accessing the same operational customer profile without duplicating data. Salesforce customers can also import their own datasets into Data Cloud. “We wanted a federated data model,” Jania said. “If you’re using Snowflake, for example, we virtually sit on your data lake, providing value by forming comprehensive operational customer profiles.” Understanding Einstein Copilot “Copilot means having an assistant within the tool you’re using, contextually aware of your tasks and assisting you at every step,” Jania said. For marketers, this could start with a campaign brief created with Copilot’s help, identifying an audience, and developing content. “Einstein Studio is exciting because customers can create actions for Copilot that we hadn’t even envisioned.” Contrary to previous reports, there is only one Copilot, Einstein Copilot, with various use cases like marketing, merchants, and shoppers. “We use these names for clarity, but there’s just one Copilot. You can build your own use cases in addition to the ones we provide.” Marketers will need time to adapt to Copilot. “Adoption takes time,” Jania acknowledged. “This Connections event offers extensive hands-on training to help people use Data Cloud and these tools, beyond just demonstrations.” What’s New with Einstein Personalization Einstein Personalization is a real-time decision engine designed to choose the next best action or offer for customers. “What’s new is that it now runs natively on Data Cloud,” Jania explained. While many decision engines require a separate dataset, Einstein Personalization evaluates a customer holistically and recommends actions directly within Service Cloud, Sales Cloud, or Marketing Cloud. Ensuring Trust Connections presentations emphasized that while public LLMs like ChatGPT can be applied to customer data, none of this data is retained by the LLMs. This isn’t just a matter of agreements; it involves the Einstein Trust Layer. “All data passing through an LLM runs through our gateway. Personally identifiable information, such as credit card numbers or email addresses, is stripped out. The LLMs do not store the output; Salesforce retains it for auditing. Any output that returns through our gateway is logged, checked for toxicity, and only then is PII reinserted into the response. These measures ensure data safety beyond mere handshakes,” Jania 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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May 30, 2024in Einstein 1 Platform, Generative AI, Hyperforce, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Snowflake
Growing Family of Einstein Copilots
27May

Growing Family of Einstein Copilots

Salesforce made several announcements this month, regarding the Growing Family of Einstein Copilots. By unveiling AI-powered Einstein Copilots for marketing and merchants. These new Copilots build on the previously announced Copilots for retailers and shoppers and are integrated into the Einstein 1 platform. They can communicate with each other, effectively bridging marketing and commerce, and have full access to Salesforce Data Cloud. “Welcome to the AI enterprise,” said Ariel Kelman, Salesforce President and CMO, during his keynote at Salesforce Connections in Chicago. Kelman outlined four waves of AI: Predictive (e.g., lead scoring), Generative, Autonomous, and AI General Intelligence. “We are starting to enter the third wave,” he stated, where AI will begin to take actions independently. Copilots are a step in that direction, although for now, a human remains in control. The Path to the AI Enterprise Kelman described five steps towards creating an AI enterprise: Regarding the last point, new Slack AI tools were demonstrated for summarizing interactions and importing actionable data from Data Cloud into Slack. The strategy for Einstein Copilots aims to empower business users in marketing, commerce, and other functions to execute complex tasks, such as creating personalized customer journeys, using natural language prompts. Einstein Copilots for Marketing and Merchants The marketing Copilot can generate marketing briefs and content, and create email campaigns. Through Data Cloud, it can ingest and execute a brand’s datasets, including customer data from repositories like AWS, Snowflake, and Databricks. By automating routine tasks and time-consuming projects like data connection and analysis, the Copilot aims to free up marketers to engage more thoughtfully with their audiences. The commerce Copilot, part of Salesforce’s commerce offerings, responds to natural language prompts to create online storefronts, improve product discoverability, write product descriptions, and make product recommendations. Other Announcements Availability 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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May 27, 2024in Einstein 1 Platform
AI Powered Education Cloud
25May

AI Powered Education Cloud

Salesforce Unveils New AI-Powered Features for Education Cloud Salesforce recently announced a suite of new features for its Education Cloud platform designed to simplify tasks for educators and students. AI Powered Education Cloud is here. These features range from student-focused tools, such as helping students stay on track with their degree requirements, to admin-focused capabilities like standardizing an institution’s entire student data corpus. New AI Capabilities Available in June Features Coming in October Enhancing Education with AI Salesforce positions these new features as tools to alleviate teacher burnout and enhance student career prospects. “With industry-specific AI and data tools, Education Cloud will help K-12 and higher ed institutions provide more individualized support for every student while increasing efficiency and helping to reduce staff burnout,” said Salesforce Vice President Bala Subramanian in a prepared statement. “This will free educators and staff to focus on improving student outcomes like career readiness, well-being, and graduation rates.” 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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May 25, 2024in Einstein 1 Platform, Salesforce, Salesforce Education Cloud, Salesforce Education Solutions
IBM Salesforce AI Partnership
25May

IBM Salesforce AI Partnership

IBM and Salesforce Expand Partnership to Advance Open, Trusted AI and Data Ecosystems PR Newswire-IBM Salesforce AI Partnership ARMONK, N.Y. and SAN FRANCISCO, May 21, 2024 – IBM (NYSE: IBM) and Salesforce (NYSE: CRM) today announced an expanded strategic partnership designed to bring together IBM’s watsonx AI and Data Platform with the Salesforce Einstein 1 Platform. This collaboration aims to provide greater customer choice and flexibility in AI and data deployment, empowering teams to make data-driven decisions seamlessly. Key Highlights of the Expanded Partnership: 1. Enhanced Large Language Models for Generative AI: The IBM watsonx platform and IBM Granite series models will introduce more large language models (LLMs) to support generative AI use cases across the Salesforce Einstein 1 Platform. This integration will provide pre-built actions and prompts, enhancing AI capabilities for CRM solutions. 2. Zero Copy Data Integration: IBM joins the Salesforce Zero Copy Partner Network to enable secure, zero-copy data integration between IBM watsonx and Salesforce Data Cloud. This integration offers customers a cost-effective way to connect and leverage their data without the need to move it, ensuring seamless data access and actionability. 3. Commitment to Responsible AI: Salesforce has joined the AI Alliance, reinforcing its commitment to developing open, safe, and responsible AI. This collaboration aims to foster transparency and ethics in AI development, aligning with the AI Alliance’s mission to advance beneficial AI innovation. Integration Details: Large Language Model Flexibility: Organizations can deploy generative AI for CRM use cases with LLMs tailored to their business needs. Salesforce’s “Bring Your Own Large Language Model” strategy allows customers to integrate their LLMs with the watsonx.ai platform and Salesforce Einstein 1 Studio. This will provide access to IBM’s Granite series AI models and custom LLMs built on watsonx, enhancing AI-driven customer interactions. Industry-Specific Solutions: Together with IBM Consulting, Salesforce will offer industry-specific prompt templates and copilot actions in Einstein 1 Studio, starting with public sector use cases. These templates are designed to optimize both foundation and Granite models for various industries, including automotive, energy, financial services, and public sector. Bidirectional Data Integration: By joining the Salesforce Zero Copy Partner Network, IBM enables bidirectional data integration with Salesforce Data Cloud. This integration allows customers to access IBM data via watsonx.data within Salesforce Data Cloud, maintaining data security and minimizing risks. This approach simplifies data management, maximizing technology investments and ensuring comprehensive data accessibility for analytics and AI. Industry Impact: Ritika Gunnar, General Manager of Product Management, Data and AI at IBM, emphasized the importance of choosing the right foundation models for AI strategies, stating, “IBM and Salesforce are making it easier for clients to navigate the complex generative AI landscape by helping them select the right LLM for their business needs.” Rahul Auradkar, EVP & GM of United Data Services & Einstein at Salesforce, highlighted the benefits of the partnership, saying, “With bidirectional data integration, companies can harmonize all their data faster, fueling actionable insights that empower teams to make data-driven decisions and deliver integrated experiences across all customer touchpoints.” About IBM: IBM is a global leader in hybrid cloud and AI, providing consulting expertise to clients in over 175 countries. IBM’s innovations in AI, quantum computing, and industry-specific cloud solutions support digital transformations with a commitment to trust, transparency, and inclusivity. For more information, visit www.ibm.com. About Salesforce: Salesforce is the #1 AI CRM, helping companies connect with customers through CRM + AI + Data + Trust on one unified platform, Einstein 1. For more information, visit www.salesforce.com. For additional details on IBM Granite and the partnership with Salesforce, visit IBM Granite. Statements regarding IBM’s and Salesforce’s future directions are subject to change and represent goals and objectives only. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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May 25, 2024in Einstein 1 Platform, Generative AI, Salesforce Data Cloud

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