Salesforce Einstein Archives - gettectonic.com - Page 10
What is Salesforce Einstein 1
09Apr

What is Salesforce Einstein 1?

The bold new future of enterprise AI requires a new type of platform. What is Salesforce Einstein 1? One platform that can handle terabytes of disconnected data, gives you the freedom to choose your AI models, and connects directly into the flow of work, all while maintaining customer trust. The Einstein 1 Platform unifies your data, AI, CRM, development, and security into a single, comprehensive platform. It empowers IT, admins, and developers with an extensible AI platform, facilitating fast development of generative apps and automation. What is Salesforce Einstein 1 Einstein 1 has a mixture of artificial intelligence tools on the platform, and it kind of mirrors the way the core Salesforce platform is built, standardized and custom. We have out of the box AI features such as sales email generation in Sales Cloud, and service replies in Service Cloud. What is Einstein One? Einstein One seamlessly integrates our robust data platform with Data Cloud, offering a comprehensive AI and data-driven solution within our CRM service. As the leading comprehensive AI for CRM, Salesforce Einstein transforms the Customer Success Platform by incorporating a suite of integrated AI technologies, making it more intelligent and accessible to innovators worldwide. Introducing the Einstein One Platform The future of enterprise AI demands a groundbreaking platform capable of managing terabytes of diverse data, providing the flexibility to select AI models, and seamlessly integrating into daily workflows while maintaining customer trust. The Einstein One Platform consolidates data, AI, CRM, development, and security into a singular, comprehensive platform. It empowers IT, administrators, and developers with an extensible AI platform, facilitating rapid development of generative apps and automation. Salesforce has made significant investments in enhancing the Einstein One platform by introducing two prompt engineering features – a testing center and prompt engineering suggestions, demonstrating the company’s commitment to advancing AI capabilities. Data-driven and AI-driven customer experiences are vital in constructing Data Cloud. Salesforce’s predictive AI, Einstein, has been operational since 2016, conducting over a trillion predictions per week. The company continuously evolves its capabilities, introducing generative AI products like Einstein GPT, discussed at Dreamforce [2023]. ‘Customer 360′ now represents Salesforce customers’ ability to transform into customer-centric entities, delivering integrated and cohesive experiences across sales, marketing, service, and commerce. Leveraging Data Cloud, structured and unstructured engagement data comes alive, offering a personalized perspective of customer interactions. Einstein is accessible through various Salesforce products, including Sales Cloud, Service Cloud, Marketing Cloud, Salesforce Platform, Analytics Cloud, and Community Cloud. What is the Einstein One platform? Salesforce’s Einstein One is a transformative platform that securely integrates data, connects multiple Salesforce products, and empowers customer-centric businesses to create AI-driven apps, revolutionizing CRM interactions. What applications are connected with the Einstein One platform? Einstein Trust Layer: Ensuring the security of generative AI applications within Salesforce, this application acts as a safeguard for data, preventing unauthorized access. Data Cloud: Unifying structured and unstructured data, Data Cloud completes the customer 360 profile, integrating seamlessly with the Einstein One platform and making data actionable. Einstein Copilot: A built-in conversational assistant, Einstein Copilot enables users to ask questions in Natural Language and receive intelligent answers, actions, and more. Copilot Studio: An essential component of Einstein One, Copilot Studio manages Einstein One and Einstein Copilot, allowing businesses to control user access and use generative AI in their workspace. Prompt Builder, Skill Builder, Model Builder: Tools within Copilot Studio, these components empower businesses to create trusted AI prompts, add skills to user access, and choose AI models. What is Data Cloud for Einstein One? Data Cloud, combined with the Einstein Trust Layer, provides secure access to a unified data repository, forming a reliable resource for complete customer profiles and supporting AI assistants. Data Cloud facilitates valuable visualizations through reports, dashboards, and tools like Tableau, offering insights to enhance understanding of customers and business operations. What will Einstein One do for businesses? Einstein One aims to: Increase productivity Reduce operational costs Enhance the delivery of exceptional customer experiences The debut of Einstein One marks a significant stride for Salesforce and businesses, offering a secure path to boost productivity through AI technologies, ensuring continuous access to cutting-edge technologies for businesses. Where can generative AI impact businesses today? Generative AI has the potential to impact businesses by enhancing repetitive processes, making them faster. Exploring text-based processes, such as repetitive emails or form filling, is a great starting point for businesses looking to enhance capabilities. What can generative AI do for sales, service, field service teams? Generative AI can positively impact teams by automating processes, offering intelligent insights, and improving overall efficiency. Specific use cases for generative AI in sales, service, and field service teams can be explored through Salesforce’s 101 video series. What does Einstein One Tableau do? Einstein One Data Cloud, formerly known as Genie, serves as a metadata management tool connecting data from various sources. It makes data usable for AI and analysis, integrating with Einstein One, Tableau, and Salesforce’s CRM applications. Is Salesforce Einstein the same as Tableau? Formerly known as Einstein Analytics, Tableau CRM is Salesforce’s premium analytic platform, offering a powerful way to explore data, especially for current Salesforce users. Salesforce has renamed Einstein Analytics to Tableau CRM, reflecting its commitment to empowering users to make better decisions faster. In essence, the Einstein One platform combines Salesforce Data Cloud, Einstein Copilot, and the Einstein Trust Layer, providing a comprehensive solution for secure and connected data, facilitating generative AI on a comprehensive platform. Salesforce’s Einstein One Platform & the Data-Driven Revolution This innovation has the potential to revolutionize the way businesses interact with their customers. In this insight, we delve deeper into this transformative development, offering valuable insights, considerations for implementation, and the indispensable expertise of Tectonic as a data-oriented technology partner. Salesforce Data Cloud and Einstein AI are now seamlessly integrated into the Einstein One Platform. This integration empowers companies to effortlessly connect their diverse data sources, enabling the creation of AI-driven applications with minimal coding effort. Moreover, it forges a cohesive view of your data across

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April 9, 2024in Artificial Intelligence, Data, Einstein 1 Platform, Einstein Insights, Enterprise, Generative AI, Google, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Salesforce Sales Cloud, Technology
08Apr

Public Sector Solutions Record Aggregation

Public Sector Solutions Record Aggregation to Simplify Information Access for Caseworkers Caseworkers often need to review benefit applications and associated benefits for household members to determine eligibility. However, this process can be complex due to the indirect relationship between benefit assignments and party relationship groups. Caseworkers must navigate through multiple objects to access this information, which can be time-consuming and inefficient. Record aggregation offers a solution to this challenge by allowing caseworkers and other users to easily access information from two unrelated objects. With record aggregation, records from one object (e.g., benefit assignments) are aggregated and linked to records of another unrelated object (e.g., party relationship group). This consolidated view helps users quickly access relevant information without navigating through multiple layers of data. Setting Public Sector Solutions Record Aggregation To implement record aggregation: Benefits of Record Aggregation Record aggregation enables: By leveraging record aggregation, public sector organizations can streamline processes for caseworkers and enhance efficiency in benefit application reviews. This approach ensures that relevant information is readily available, ultimately improving service delivery and decision-making. 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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April 8, 2024in Public Sector Solutions, Salesforce Einstein
Salesforce Einstein
05Apr

Einstein Opportunity Scoring Explained

Utilize Artificial Intelligence to Optimize Opportunity Management: Einstein Opportunity Scoring Explained Let artificial intelligence (AI) empower you and your team to focus on the most promising opportunities and maximize deal closure rates. Each opportunity is assigned a score ranging from 1 to 99, providing valuable insights into its potential outcome. These scores are readily available on opportunity records and list views, ensuring easy access to critical information. Moreover, if you utilize Collaborative Forecasts, opportunity scores are also integrated into the forecasts page, enhancing visibility and forecasting accuracy. Einstein Opportunity Scoring is a versatile tool accessible to users with or without a Sales Cloud Einstein license. It provides a predictive assessment of the likelihood that an opportunity will result in a successful deal. For each opportunity score generated by Einstein, users gain visibility into the key factors influencing the score, both positively and negatively. In the Lightning Experience interface, opportunity scores are conveniently displayed on the compact layout of opportunity records or on the Details tab. Hovering over the score reveals a breakdown of the contributing factors, allowing users to understand why a particular score was assigned. For instance, a high score may indicate that the opportunity is progressing rapidly through the sales stages compared to others. For users navigating Salesforce Classic, the opportunity score is presented on the record detail of opportunity records, accompanied by the contributing factors. Customizing Opportunity Management with Opportunity Scores: Admins have the flexibility to incorporate the Opportunity Score field into various opportunity list views, empowering users to prioritize and manage opportunities effectively. In Lightning Experience, hovering over the score in list views provides insights into the factors influencing the score. However, in Salesforce Classic, users need to navigate to the opportunity record detail page to access this information. Furthermore, for organizations leveraging Collaborative Forecasts, admins can seamlessly integrate opportunity scores into the opportunity list on the forecasts page, enhancing forecasting accuracy and sales planning. Understanding Opportunity Score Criteria: The opportunity score is derived from a comprehensive analysis of various factors, including market demand, competitive landscape, potential return on investment, and resource requirements. By considering these criteria, Einstein Opportunity Scoring provides actionable insights to guide decision-making and resource allocation. Exploring Einstein Lead Scoring Criteria: In addition to opportunity scoring, Einstein offers lead scoring functionality to identify high-quality leads. By analyzing past leads, Einstein determines which current leads share similarities with those that have previously converted. Admins can customize lead scoring criteria by including or excluding specific lead fields based on their relevance to lead quality. Sales Cloud Einstein Scoring Hierarchy: Einstein Opportunity Scoring is part of Sales Cloud Einstein Scoring, which encompasses both opportunity and lead scoring capabilities. In this hierarchy, Einstein Lead Scoring falls under the broader umbrella of Salesforce’s Sales Cloud Einstein model. Together, these scoring mechanisms empower sales teams with predictive insights to optimize their sales processes and drive success. Einstein Opportunity Scoring equips sales professionals with predictive analytics to assess opportunity viability accurately. By leveraging AI-driven scoring, organizations can streamline opportunity management, prioritize resources effectively, and ultimately, enhance sales performance and revenue growth. Like1 Related Posts 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more

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April 5, 2024in Einstein Insights, Salesforce Einstein
Salesforce Generative AI
03Apr

Is Slack Secure?

Slack and AI are here. Seems Promising, but Is Slack Secure? At Slack and Salesforce, trust is paramount. When it comes to AI, security is the top concern voiced by their customers. They are dedicated to developing AI products that are safe, responsible, and ethical. Their decision-making is guided by a set of product values aimed at upholding your trust. Is slack secure? You Maintain Control Over Your Data In a landscape where some companies view customer data as a commodity, Salesforce and Slack prioritize user safety and data privacy. Their new AI features are integrated within Slack’s secure infrastructure, ensuring that your data remains under your control. They neither sell, rent, nor utilize your information for commercial purposes because they firmly believe that your trust cannot be bought. Slack does not share customer data with large language model (LLM) providers nor utilize customer data to train LLMs. Slack AI operates on Slack’s infrastructure, adhering to the same stringent security practices and compliance standards expected from Slack itself. The entire ecosystem upholds a high level of security and compliance, including features like Enterprise Key Management, which empowers customers to manage their encryption keys independently. You Can Verify Results Tectonic recognizes that trust in technology hinges on its integrity. Slack AI features are designed to be transparent, allowing you to delve into the results and independently verify them. AI should complement, not replace, human judgment, and our aim is to provide tools that empower users to make informed decisions. Explore More AI Tools in Slack Today Slack’s AI capabilities are both subtle and powerful, complemented by a growing array of third-party AI apps vetted for reliability. One such app is Claude, a conversational chatbot from Anthropic available to Slack Enterprise Grid users. Claude functions as a knowledgeable personal assistant, adept at tasks like account planning, contract reviews, and strategy generation, all while maintaining privacy. Using Claude is straightforward; simply tag @Claude in channels or group messages to initiate tasks visible to your team. Additionally, Slack offers integration with other AI-powered apps such as Box, PagerDuty, Perplexity, and Notion, enhancing collaboration and efficiency. This Is Just the Beginning As Salesforce and Slack introduce user-friendly AI tools in Slack, they’re opening doors to limitless possibilities. Starting with robust features designed to simplify and streamline work processes, they plan to unveil more intelligent features aimed at helping teams maximize their organizational impact. 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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April 3, 2024in Salesforce, Salesforce Einstein, Salesforce Slack
Salesforce's Get Ready for AI Report
01Apr

Salesforce’s Get Ready for AI Report

Welcome to the future of business – Get Ready for AI is for analytics and data leaders. The tools for those who are interested in positioning themselves for AI success. From strategy to governance, you’ll learn what’s top-of-mind with other thought leaders, and see what actions you can take to be a more effective leader in a rapidly changing technology and business environment.  Salesforce’s Get Ready for AI Report This insight introduces four topics that are essential for data leaders beginning their AI journey: Access the full report here. Salesforce’s Get Ready for AI Report Data is at the center of any AI initiative, and organizations that are leading the way are focused on ensuring their data sources are current, authoritative, and complete. From talent, to strategy, to infrastructure, organizations that are prioritizing data across every business unit are ready to ride the AI wave. Positioning themselves for a significant competitive advantage over their peers. Salesforce’s Get Ready for AI Report As with any digital transformation, success depends on an enterprise-wide commitment. Data leaders are in a unique position to help guide their organizations through this transition, and achieve the benefits that AI can deliver. 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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April 1, 2024in Salesforce, Salesforce Einstein
AI Then and Now
30Mar

AI Then and Now

AI: Transforming User Interactions and Experiences Have you ever been greeted by a waitress who already knows your breakfast order? It’s a relief not to detail every aspect — temperature, how do you want your eggs, what kind of juice, bacon or sausage, etc. This example encapsulates the journey we’re navigating with AI today. AI Then and Now. This article isn’t about ordering breakfast; it’s about the evolution of user interactions, particularly how generative AI might evolve based on past trends in graphical user interfaces (GUIs) and emerging trends in AI interactions. We’ll explore the significance of context bundling, user curation, trust, and ecosystems as key trends in AI user experience in this Tectonic insight. From Commands to Conversations Let’s rewind to the early days of computing when users had to type precise commands in a Command-Line Interface (CLI). Imagine the challenge of remembering the exact command to open a file or copy data. This complexity meant that only a few people could use computers effectively. To reach a broader audience, a shift was necessary. You might think Apple’s creation of the mouse and drop down menues was the pinnacle of success, but truly the evolution predates Apple. Enter ELIZA in 1964, an early natural language processing program that engaged users in basic conversations through keyword recognition and scripted responses. Although groundbreaking, ELIZA’s interactions were far from flexible or scalable. Around the same time, Xerox PARC was developing the Graphical User Interface (GUI), later popularized by Apple in 1984 and Microsoft shortly thereafter. GUIs transformed computing by replacing complex commands with icons, menus, and windows navigable by a mouse. This innovation made computers accessible and intuitive for everyday tasks, laying the groundwork for technology’s universal role in our lives. Not only did it make computing accessible to the masses but it layed the foundation upon which every household would soon have one or more computers! The Evolution of AI Interfaces Just as early computing transitioned from the complexity of CLI to the simplicity of GUIs, we’re witnessing a parallel evolution in generative AI. User prompts are essentially mini-programs crafted in natural language, with the quality of outcomes depending on our prompt engineering skills. We are moving towards bundling complex inputs into simpler, more user-friendly interfaces with the complexity hidden in the background. Context Bundling Context bundling simplifies interactions by combining related information into a single command. This addresses the challenge of conveying complex instructions to achieve desired outcomes, enhancing efficiency and output quality by aligning user intent and machine understanding in one go. We’ve seen context bundling emerge across generative AI tools. For instance, sample prompts in Edge, Google Chrome’s tab manager, and trigger-words in Stable Diffusion fine-tune AI outputs. Context bundling isn’t always about conversation; it’s about achieving user goals efficiently without lengthy interactions. Context bundling is the difference in ordering the eggs versus telling the cook how to crack and prepare it. User Curation Despite advancements, there remains a spectrum of needs where users must refine outputs to achieve specific goals. This is especially true for tasks like researching, brainstorming, creating content, refining images, or editing. As context windows and multi-modal capabilities expand, guiding users through complexity becomes even more crucial. Humans constantly curate their experiences, whether by highlighting text in a book or picking out keywords in a conversation. Similarly, users interacting with ChatGPT often highlight relevant information to guide their next steps. By making it easier for users to curate and refine their outputs, AI tools can offer higher-quality results and enrich user experiences. User creation takes ordering breakfast from a manual conversational process to the click of a button on a vending-like system. Designing for Trust Trust is a significant barrier to the widespread adoption of generative AI. To build trust, we need to consider factors such as previous experiences, risk tolerance, interaction consistency, and social context. Without trust, in AI or your breakfast order, it becomes easier just to do it yourself. Trust is broken if the waitress brings you the wrong items, or if the artificial intelligence fails to meet your reasonable expectations. Context Ecosystems Generative AI has revolutionized productivity by lowering the barrier for users to start tasks, mirroring the benefits and journey of the GUI. However, modern UX has evolved beyond simple interfaces. The future of generative AI lies in creating ecosystems where AI tools collaborate with users in a seamless workflow. We see emergent examples like Edge, Chrome, and Pixel Assistant integrating AI functionality into their software. This integration goes beyond conversational windows, making AI aware of the software context and enhancing productivity. The Future of AI Interaction Generative AI will likely evolve to become a collaborator in our daily tasks. Tools like Grammarly and Github Copilot already show how AI can assist users in creating and refining content. As our comfort with AI grows, we may see generative AI managing both digital and physical aspects of our lives, augmenting reality and redefining productivity. The evolution of generative AI interactions is repeating the history of human-computer interaction. By creating better experiences that bundle context into simpler interactions, empower user curation, and augment known ecosystems, we can make generative AI more trustworthy, accessible, usable, and beneficial for everyone. 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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March 30, 2024in AI Tools, Artificial Intelligence, Data, Generative AI, Google, Salesforce, Salesforce Einstein, Technology
Salesforce Einstein
25Mar

Use AI to Prep for Meetings

Sales is fundamentally a relationship-oriented endeavor, where representatives invest substantial time delving into lead interests, needs, and behaviors to fortify connections. What if you could Using AI to prep for meetings? Imagine a tool that assumes this responsibility, endowing you with the ability to swiftly acquaint yourself with pertinent information. Here’s what AI can accomplish: it undertakes the arduous research, analyzing both public and CRM data to succinctly encapsulate vital prospect details essential for pre-meeting preparation. If you have specific queries, just pose a question, and AI promptly provides a powered response. Consider this scenario: A sales representative steps in for a colleague on leave, aiming to catch up on major accounts. They leverage Einstein in Sales Cloud, filtering deals with a revenue exceeding $100,000. Many of these deals boast extensive historical data, a formidable amount to sift through. Einstein streamlines the process by presenting deal summaries encompassing crucial information such as involved parties, recent activities, potential risks, and recommended next steps. How to use AI to prep for meetings Einstein goes a step further, flagging an email from a customer with pricing queries awaiting a response. The rep seeks guidance: “What key information should I know about this customer before addressing the email?” Einstein synthesizes the deal in plain language, offering key account details and insights from past meetings to seamlessly resume the conversation. In other words, Einstein answers the reps question – in seconds. Sales Summaries for Sales Cloud becomes the go-to solution for instant meeting preparation, enabling sellers to navigate meetings with agility. Elevate your selling velocity with integrated AI directly in your CRM. Provide each seller with an AI assistant to turbocharge sales across the cycle, automating tasks, expediting decisions, and steering sellers towards swift closures. Einstein 1 allows effortless customization and integration of AI into various workspaces. Here are some key functionalities: 1. Call Summaries & Exploration: Bid farewell to tedious note-flipping. Ask Einstein to synthesize critical call information swiftly, generating concise summaries or identifying pivotal takeaways and customer sentiment from sales calls. 2. Prospect and Account Research: Streamline research on prospects and accounts. Summarize CRM records to gauge deal viability, competitor involvement, and more. Fetch real-time data updates from the news, and direct Einstein to update lead or opportunity records effortlessly. 3. Call Insights: Identify crucial moments from sales conversations. Instantly recognize objections, pricing attitudes, and questions asked without sifting through entire calls. Accelerate deal progression with conversation insights related to opportunities. 4. Relationship Graphs: Discern relationship networks effortlessly. Grasp prospect and customer networks for each deal, with automatic population of contacts and relevant details to fortify relationships with decision-makers. 5. Relationship Insights: Unearth new relationship insights with support from external data. Gain vital context from diverse sources across the web, seamlessly integrated into your CRM, and automatically update existing records with newfound information. Generative AI for Sales: Generative AI employs straightforward prompts to craft copy (e.g., prospecting emails) and provide recommendations (e.g., suggestions for quick-win deals). It analyzes existing sales and customer data to assist in drafting emails and determining messages or resources that would propel a sales conversation forward. Integration into a CRM, the hub of sales and customer data, is the likely destination for these capabilities. And while we’re at it – Real-Time Improvement of Sales Presentations: Crafting compelling presentations demands significant time and effort. Generative AI, activated through text-based prompts in presentation tools, facilitates the creation of customized decks and pitches within minutes. Early versions of real-time coaching are emerging, where AI-based guidance, embedded in video conferencing tools, evaluates live presentations to ensure they address the prospect’s pain points effectively. This advanced system, triggered by specific keywords, can recommend prospect-specific information, transforming your presentation into a tailored and impactful experience. Like Related Posts 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more

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March 25, 2024in Einstein Insights, Generative AI, Salesforce Einstein
Salesforce Education Cloud for Educational Challenges
24Mar

Salesforce Education Cloud for Educational Challenges

Educational institutions today confront a multitude of complex challenges, ranging from disjointed information systems to the need for agility in meeting evolving educational demands. Salesforce Education Cloud presents a unified solution aimed at overcoming these obstacles by enhancing operational efficiencies, boosting student engagement, and ensuring compliance with ever-changing educational standards. Below is an in-depth examination of the prevalent challenges faced by educational institutions and the tailored solutions provided by Salesforce Education Cloud. Key Challenges in the Education Sector Salesforce Education Cloud: Tailored Solutions for Education Salesforce Education Cloud addresses these challenges through a suite of customized features and tools designed to streamline operations, enhance student services, and promote effective communication. Real-World Impact of Salesforce Education Cloud Implementation of Salesforce Education Cloud yields transformative benefits across educational institutions: Conclusion Salesforce Education Cloud offers a comprehensive solution to the diverse challenges faced by educational institutions. By integrating this robust platform, schools, colleges, and universities can enhance operational efficiency, improve student outcomes, and cultivate a collaborative educational environment. Institutions seeking to explore the benefits of Education Cloud or enhance their existing systems are encouraged to consult with a Salesforce Education Cloud Consultant for tailored guidance and implementation strategies. 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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March 24, 2024in Salesforce, Salesforce Education Cloud, Salesforce Education Solutions, Salesforce Einstein
Gov Agencies AI Workforce Challenges
24Mar

Gov Agencies AI Workforce Challenges

Federal agencies are placing a higher priority on providing AI training to their workforces with a focus on principles of transparency and accountability, officials announced at ATARC’s GITEC conference in Charlottesville, Virginia earlier. Gov Agencies AI Workforce Challenges. Alexis Bonnell, Air Force Research Laboratory CIO and Director of the Digital Capabilities Directorate, emphasized the importance of upholding existing ethics standards rather than creating new ones. She stressed that agencies need to exercise the ethical principles they have always been expected to follow. President Biden’s October 2023 executive order on artificial intelligence mandated that agencies develop ethical AI and establish AI offices, among other directives. While agencies like the Defense Department and the Department of Homeland Security are optimistic about AI’s potential, leaders remain cautious about its ethical implications and stress the importance of safe technology development. It’s not just technologists who require AI training. To ensure all employees understand AI’s risks and benefits, government leaders are prioritizing education and upskilling efforts. Steven Brand, Energy Deputy CIO of Resource Management, highlighted the initiative to provide foundational AI training across his department, emphasizing that the goal is not to make employees experts. Tammy Hornsby-Fink, Executive Vice President and System CISO at the Federal Reserve Bank of Richmond, emphasized the need for accessible learning opportunities for all department members, from data scientists to executive assistants, to grasp AI concepts in manageable increments. Hornsby-Fink also emphasized the importance of providing sandboxes for employees to experiment with new technologies safely, stressing that experimentation is key to understanding how these technologies can create business value. According to Tony Boese, Department of Veterans Affairs Interagency Programs Manager, consistent education is essential to combat misinformation about AI. He mentioned the agency’s ASPIRE data-literacy program, which leverages AI to identify skills gaps and tailor educational pathways for individuals. Karen Howard, IRS Office of Online Services Executive Director, highlighted the need to modernize recruitment strategies and change management principles to attract top talent and leverage digital transformation and AI effectively. Jamie Holcombe, U.S. Patent and Trademark Office CIO, emphasized the importance of diversifying agency workforces by bringing in new perspectives from industry, such as those from Silicon Valley, to move away from outdated organizational playbooks. Gov Agencies AI Workforce Challenges 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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March 24, 2024in Salesforce Einstein
Learning AI
21Mar

The New Age of Compliance with AI

How can small businesses ensure compliance? Business in the New Age of Compliance with AI can be challenging. While larger corporations often allocate resources for extensive research and development to maintain compliance, smaller businesses may lack the means to conduct thorough due diligence. In such cases, it becomes crucial for them to pose the right questions to vendors and technology partners within their ecosystem. Even as Salesforce takes strides in creating trustworthy generative AI solutions for its customers, these customers also engage with other vendors and processors. It is imperative for them to remain vigilant about potential risks and not rely solely on trust. Salesforce and Tectonic suggest that smaller companies should inquire about: For smaller companies, depending on the due diligence of third-party service providers becomes essential. Evaluating privacy protocols, security procedures, identification of potential harms, and safeguarding measures are critical aspects that demand close attention. In this New Age of Compliance with AI everyone is responsible. Choosing an AI savvy Salesforce partner like Tectonic protects you and your company. The Einstein Trust Layer is your insurance that you are doing artificial intelligence right. 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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March 21, 2024in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Einstein
Custom Copilot Actions
18Mar

Custom Copilot Actions

How to Create a Custom Copilot Action Custom Copilot Actions allow you to extend Copilot’s functionality within Salesforce, enabling users to perform tasks specific to your business needs. By utilizing invocable Apex classes, autolaunched flows, and prompt templates, you can build custom actions tailored to your organization’s requirements. Extend your unified copilot with custom actions. Before You Begin: Steps to Create a Custom Copilot Action: Testing and Deployment: Understanding Einstein Copilot Einstein Copilot is Salesforce’s AI assistant designed to enhance productivity and user experience across various applications and departments. Admins can configure and deploy Copilots to empower users with AI capabilities, streamlining workflows and increasing efficiency. Out-of-the-Box Actions: In the Spring ’24 release, Einstein Copilot offers several out-of-the-box actions, including: Customization and Future Development: Admins can create custom actions to tailor Copilot’s capabilities to their organization’s specific requirements. Custom actions enable tasks such as updating records and integrating with external systems, enhancing productivity and efficiency. When you create a custom action, you build it on top of platform functionality you want to make available in Einstein Copilot, such as invocable Apex classes, autolaunched flows, or prompt templates. Adding custom actions lets you customize your copilot and get more mileage out of your current Salesforce platform capabilities. Access to a custom copilot action depends on the type of Salesforce action it references. For example, if a custom action was built using a flow, the custom action adheres to the permissions, field-level security, and sharing settings configured in the flow. Use Cases and Considerations: Typical Use Cases: Considerations: Building Custom Copilot Actions: Power of Custom Actions: Custom actions extend Copilot’s capabilities, offering a wide range of use cases and functionalities. Actions can be built using flows, prompts, or Apex, providing flexibility and customization options. Descriptive Instructions: Accurate descriptions of actions, inputs, and outputs are essential for Copilot’s understanding and execution. Clear instructions provide context and improve response accuracy. Best Practices: Einstein Copilot, coupled with custom actions, empowers organizations to optimize workflows and drive efficiency. By following best practices and leveraging the full potential of Copilot, Salesforce admins can enhance user experiences and unlock new levels of productivity. Explore these features within your organization to realize the benefits of Salesforce Einstein Copilot Custom Actions. Assign an action to your copilot from the Copilot Actions page, the record page for an action, or the Copilot Action Library tab of the actions panel in the Copilot Builder. Your copilot must be deactivated. To test your action and preview how the output appears in a copilot conversation, open the copilot in the Copilot Builder and start a preview conversation. Enter utterances that you expect to trigger your action, and then make adjustments to the copilot action instructions based on your results. What powers Einstein Copilot custom actions? By facilitating the flow of work through smart, AI-driven actions, Einstein Copilot enhances efficiency and decision-making. Here’s how organizations can harness its power through the design of custom actions, ensuring their operations are as streamlined and effective as possible. 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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March 18, 2024in Mulesoft, Salesforce Einstein
Learning AI
16Mar

AI Success is a Team Sport

The contemporary workplace is currently experiencing a profound transformation. The Future of Jobs Report from the World Economic Forum predicts that AI will replace approximately 85 million jobs by 2025, while concurrently generating around 97 million AI-related jobs. AI Success is a Team Sport and will require hiring and training people. This significant shift necessitates a reevaluation of work dynamics, introducing new roles that involve collaboration between “humans, machines, and algorithms.” Amidst this transformative period, AI provides opportunities for organizations to reimagine existing roles, offer upskilling opportunities, and design innovative positions to meet evolving needs. For leaders in the data domain, the crucial task is to assess which jobs could benefit from AI. This requires a thorough understanding of organizational tasks, skills, and strategic goals, complemented by a scalable change management process to accommodate the growth of AI initiatives. To pinpoint relevant jobs, the following steps can be taken: Despite 67% of global business leaders considering the use of generative AI, an equal number of IT leaders acknowledge a skills gap among their employees. “I think most business leaders have a good sense of what the key jobs are inside their organizations. Of those key jobs, what are the good candidates for AI? I think it’s important for any executive—data or not—to understand what they are and plan accordingly.” SOLOMON KAHN DATA LEADERSHIP COLLABORATIVE  The implementation of AI necessitates a specialized team, encompassing roles from project managers to domain experts. The composition of the team depends on the project’s complexity, scope, budget, and overall strategic objectives. But to be sure, AI Success is a Team Sport. Key roles for AI initiatives include: AI acts as a disruptor to traditional business practices, and this disruption is viewed positively. The bonuses far outweigh the challenges. The new generation of user-friendly AI technologies, such as generative AI, has moved beyond the hype cycle, offering applications that generate personalized offers and automated chatbots capable of solving complex customer support issues. In this era powered by AI, data leaders play a pivotal role in driving transformative change. 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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March 16, 2024in Salesforce Einstein
LLMs Beyond Generative AI
16Mar

LLMs Beyond Generative AI

Beyond Text Generation: The Versatile Capabilities of Large Language Models While large language models (LLMs) and generative AI have dominated the conversation over the past year, the spotlight has largely been on their text generation capabilities. There’s no denying the value of LLMs in generating answers to questions. However, focusing solely on this use case overlooks other valuable applications. This insight will explore several primary uses of LLMs, ensuring you recognize their broader potential beyond just generative purposes. Creation and Generation This is the most publicized use case for LLMs today. Applications like ChatGPT can answer questions with detailed responses, and tools like DALL-E generate images based on user prompts. Similar generators exist for code, video, and 3D virtual worlds. Interestingly, these generators share fundamental algorithmic approaches despite producing different content types—text, images, videos. Since they all process prompts, they require training to understand and decompose these prompts to guide the generation process, necessitating the use of LLMs. However, generating new content is just one aspect of what LLMs can achieve. Summarization LLMs excel at summarizing information. For instance, if you have a list of papers on your to-read list, an LLM can summarize their key themes, common points, and differences. This provides a clear baseline, helping you focus on essential aspects as you read. Summarizing content with AI tends to have a lower error risk compared to generating new content because the LLM works within the boundaries of the provided information. While it might occasionally miss a pattern or emphasize the wrong details, it’s unlikely to produce completely incorrect summaries. Translation Often underrated, translation might be one of the most impactful uses of LLMs. For example, LLMs can translate old code from obsolete languages into modern ones. An LLM generates a draft translation, which, although imperfect, can be refined by a programmer who understands the goal of the code even with limited knowledge of the original language. Human language translation also stands to benefit significantly. Soon, we’ll be able to communicate in our preferred languages, with LLMs instantly translating our words into the listener’s language. This will eliminate the need for a common language and help preserve uncommon languages by removing the communication barriers associated with them. Interpretation and Extraction LLMs are also adept at interpreting statements and triggering subsequent actions. Image generators use this approach, as do tools that handle analytical queries. For instance, asking “Please summarize this year’s sales by region and subtotal by product” allows an LLM to interpret the request, extract key parameters, and pass them to a query generator for the answer. Companies like Quaeris, which I advise, focus on this capability. Additionally, LLMs can handle tasks like sentiment analysis and customer service inquiries. They can ingest inquiries and extract relevant details, such as the product in question, the issue raised, and the requested action, to route the inquiry to the appropriate person more effectively. LLMs Beyond Generative AI The examples discussed are not exhaustive but represent some common and powerful uses of LLMs. They highlight that LLMs offer far more than just text generation. Exploring these other applications can provide significant benefits for you and your organization. Originally posted in the Analytics Matters newsletter on LinkedIn. 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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March 16, 2024in Generative AI, Salesforce Einstein
What is Einstein Used for in Salesforce?
14Mar

What is Einstein Used for in Salesforce?

Salesforce Einstein is an AI-powered platform that can be used in various ways to enhance customer experiences and streamline business operations: SalesSalesforce Einstein can help sales teams better understand customers, improve conversion rates, and close deals more quickly. For instance, it can generate sales call summaries, draft emails using customer data, and provide real-time predictions. Customer ServiceEinstein helps customer service agents resolve cases faster and provide customers with relevant information during interactions. MarketingSalesforce Einstein enables marketers to create personalized experiences and send the right content to the right customer at the right time. ITSalesforce empowers IT teams to embed intelligence across the business and create smarter apps for customers and employees. CommerceSalesforce assists retailers by recommending the best products to each customer. Salesforce also includes features to protect data privacy and security, such as the Tectonic GPT Trust Layer, which provides AI bias detection, data security, and regulatory compliance. Salesforce Einstein is the first all-inclusive AI for CRM. It’s an integrated set of AI technologies that makes the Customer Success Platform smarter and brings AI to Salesforce users everywhere. Salesforce is the only comprehensive AI for CRM. It is: Tectonic and Salesforce allow businesses to become AI-first, providing the ability to anticipate customer needs, improve service efficiency, and enable smarter, data-driven decision-making. Sales teams can anticipate next opportunities and exceed customer needs,Service teams can proactively resolve issues before they occur,Marketing teams can create predictive journeys and personalize experiences like never before,IT teams can embed intelligence everywhere and create smarter apps. AI that works for your business.Drive business productivity and personalization with predictive AI, generative AI, and agents across the Customer 360 platform. Create and deploy assistive AI experiences natively in Salesforce, allowing your customers and employees to converse directly with Agentforce to solve issues faster and work smarter. Empower service reps, agents, marketers, and others with AI tools safely grounded in your customer data to make every customer experience more impactful. What is Salesforce Einstein?As of 2024, this groundbreaking AI-based product remains a leader in the CRM industry since its release in 2016. It combines a range of AI technologies, including advanced machine learning, natural language processing (NLP), predictive analytics, and image recognition, enabling businesses to improve productivity and sustain growth. Salesforce AI BenefitsThe most significant benefits of AI are the time and efficiency gains it offers to business processes. By automating tasks, employees can focus on more strategic work. Additionally, automating repetitive tasks reduces errors and enhances operational efficiency. Saleesforce provides robust reporting features that generate valuable insights to support decision-making, helping businesses understand customer needs and identify opportunities. From a customer perspective, Salesforce ensures more meaningful and personalized experiences through advanced NLP capabilities and machine learning to better understand customer behavior. Salesforce AI FeaturesSalesforce is a feature-rich platform that leverages AI’s capabilities in Natural Language Processing, Machine Learning, and image processing. Some of the key features include: Salesforce PricingCosts depend on the required features and the size of the business. Pricing starts at $50 per user per month, with potential increases based on the specific capabilities needed. Salesforce Tectonic ChallengesAlthough Salesforce Tectonic offers numerous benefits, companies may face challenges during integration, such as aligning it with existing systems and ensuring proper training for employees to maximize its use. How to Prepare for Salesforce Tectonic IntegrationUsing an implementation partner like Tectonic can help ensure seamless integration. A partner will assess your current Salesforce setup, recommend the right features, and guide you through the integration process. ConclusionSalesforce is a cutting-edge platform that empowers businesses to transform operations with comprehensive AI capabilities. It provides tailored solutions for sales, service, marketing, and commerce teams, enabling better customer interactions, data-driven decision-making, and increased productivity. With the right implementation partner like Tectonic, businesses can seamlessly integrate and leverage Tectonic to stay ahead in a competitive landscape. Content updated November 2024. 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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March 14, 2024in AI Tools, Data, Generative AI, Salesforce, Salesforce Einstein

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