Prompt Builder - gettectonic.com
Salesforce prompt builder

Salesforce Prompt Builder

Salesforce Prompt Builder: Field Generation Prompt Template What is a Prompt? A prompt is a set of detailed instructions designed to guide a Large Language Model (LLM) in generating relevant and high-quality output. Just like chefs fine-tune their recipes through testing and adjustments, prompt design involves iterating on instructions to ensure that the LLM delivers accurate, actionable results. Effective prompt design involves “grounding” your prompts with specific data, such as business context, product details, and customer information. By tailoring prompts to your particular needs, you help the LLM provide responses that align with your business goals. Like a well-crafted recipe, an effective prompt consists of both ingredients and instructions that work together to produce optimal results. A great prompt offers clear directions to the LLM, ensuring it generates output that meets your expectations. But what does an ideal prompt template look like? Here’s a breakdown: What is a Field Generation Prompt Template? The Field Generation Prompt Template is a tool that integrates AI-powered workflows directly into fields within Lightning record pages. This template allows users to populate fields with summaries or descriptions generated by an LLM, streamlining interactions and enhancing productivity during customer conversations. Let’s explore how to set up a Field Generation Prompt Template by using an example: generating a summary of case comments to help customer service agents efficiently review a case. Steps to Create a Field Generation Prompt Template 1. Create a New Rich Text Field on the Case Object 2. Enable Einstein Setup 3. Create a Prompt Template with the Field Generation Template Type 4. Configure the Prompt Template Workspace Optional: You can also use Flow or Apex to incorporate additional merge fields. 5. Preview the LLM’s Response Example Prompt: Scenario:You are a customer service representative at a company called ENForce.com, and you need a quick summary of a case’s comments. Record Merge Fields: Instructions: vbnetCopy codeFollow these instructions precisely. Do not add information not provided. – Refer to the “contact” as “client” in the summary. – Use clear, concise, and straightforward language in the active voice with a friendly, informal, and informative tone. – Include an introductory sentence and closing sentence, along with several bullet points. – Use a variety of emojis as bullet points to make the list more engaging. – Limit the summary to no more than seven sentences. – Do not include any reference to missing values or incomplete data. 6. Add the “Case Summary” Field to the Lightning Record Page 7. Generate the Summary By following these steps, you can leverage Salesforce’s Prompt Builder to enhance case management processes and improve the efficiency of customer service interactions through AI-assisted summaries. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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AI Customer Service Agents Explained

AI Customer Service Agents Explained

AI customer service agents are advanced technologies designed to understand and respond to customer inquiries within defined guidelines. These agents can handle both simple and complex issues, such as answering frequently asked questions or managing product returns, all while offering a personalized, conversational experience. Research shows that 82% of service representatives report that customers ask for more than they used to. As a customer service leader, you’re likely facing increasing pressure to meet these growing expectations while simultaneously reducing costs, speeding up service, and providing personalized, round-the-clock support. This is where AI customer service agents can make a significant impact. Here’s a closer look at how AI agents can enhance your organization’s service operations, improve customer experience, and boost overall productivity and efficiency. What Are AI Customer Service Agents? AI customer service agents are virtual assistants designed to interact with customers and support service operations. Utilizing machine learning and natural language processing (NLP), these agents are capable of handling a broad range of tasks, from answering basic inquiries to resolving complex issues — even managing multiple tasks at once. Importantly, AI agents continuously improve through self-learning. Why Are AI-Powered Customer Service Agents Important? AI-powered customer service technology is becoming essential for several reasons: Benefits of AI Customer Service Agents AI customer service agents help service teams manage growing service demands by taking on routine tasks and providing essential support. Key benefits include: Why Choose Agentforce Service Agent? If you’re considering adding AI customer service agents to your strategy, Agentforce Service Agent offers a comprehensive solution: By embracing AI customer service agents like Agentforce Service Agent, businesses can reduce costs, meet growing customer demands, and stay competitive in an ever-evolving global market. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce Einstein Copilot Security

Salesforce Einstein Copilot Security

Salesforce Einstein Copilot Security: How It Works and Key Risks to Mitigate for a Safe Rollout With the official rollout of Salesforce Einstein Copilot, this conversational AI assistant is set to transform how sales, marketing, and customer service teams interact with both customers and internal documentation. Einstein Copilot understands natural language queries, streamlining daily tasks such as answering questions, generating insights, and performing actions across Salesforce to boost productivity. Salesforce Einstein Copilot Security However, alongside the productivity gains, it’s essential to address potential risks and ensure a secure implementation. This Tectonic insight covers: Einstein Copilot Use Cases Einstein Copilot enables users to: All of these actions can be performed with simple, natural language prompts, improving efficiency and outcomes. How Einstein Copilot Works Here’s a simplified breakdown of how Einstein Copilot processes prompts: The Einstein Trust Layer Salesforce has built the Einstein Trust Layer to ensure customer data is secure. Customer data processed by Einstein Copilot is encrypted, and no data is retained on the backend. Sensitive data, such as PII (Personally Identifiable Information), PCI (Payment Card Information), and PHI (Protected Health Information), is masked to ensure privacy. Additionally, the Trust Layer reduces biased, toxic, and unethical outputs by leveraging toxic language detection. Importantly, Salesforce guarantees that customer data will not be used to train the AI models behind Einstein Copilot or be shared with third parties. The Shared Responsibility Model Salesforce’s security approach is based on a shared responsibility model: This collaborative model ensures a higher level of security and trust between Salesforce and its customers. Best Practices for Securing Einstein Copilot Rollout Prepare Your Salesforce Org for Einstein Copilot To ensure a smooth rollout, it’s critical to assess your Salesforce security posture and ready your data. Tools like Salesforce Shield can help organizations by: By following these steps, you can utilize the power of Einstein Copilot while ensuring the security and integrity of your data. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce AI Evolves with the Generative AI Landscape

Salesforce AI Evolves with the Generative AI Landscape

Salesforce AI: Powering Customer Relationship Management Salesforce is a leading CRM solution that has long delivered cutting-edge cloud technologies to manage customer relationships effectively. In recent months, the platform has further advanced with the integration of generative AI and AI-powered features, primarily through its AI engine, Einstein. Salesforce AI Evolves with the Generative AI Landscape. To explore how AI operates within the Salesforce ecosystem and how various business teams can leverage these innovations, this guide delves into Salesforce’s AI capabilities, products, and features. Salesforce AI: Transforming CRM Capabilities Salesforce remains a top choice in the CRM software market, offering one of the most comprehensive solutions for managing relationships across departments, industries, and initiatives. Through dedicated cloud platforms, Salesforce enables teams to oversee marketing, sales, customer service, e-commerce, and more, with tools focused on delivering enhanced customer experiences supported by powerful data analytics. With the introduction of generative AI, Salesforce has significantly elevated its native automation, workflow management, data analytics, and assistive capabilities for customer lifecycle management. Einstein Copilot exemplifies this innovation, aiding internal users with tasks such as outreach, analysis, and improving external user experiences. What is Salesforce Einstein? Salesforce Einstein is an AI-driven suite of tools integrated natively into various Salesforce Cloud applications, including Sales Cloud, Marketing Cloud, Service Cloud, and Commerce Cloud. It also operates through assistive technologies like Einstein Copilot. Einstein is built on a multitenant platform and incorporates numerous automated machine learning features to unify organizational data with CRM capabilities. Designed to make intelligent, data-driven decisions, Einstein requires no additional installation, offering a seamless user experience when paired with a compatible subscription plan. 7 Key Features of Salesforce Einstein 7 Applications of Salesforce Einstein Future Trends in Salesforce AI Bottom Line: Salesforce AI Evolves with the Generative AI Landscape Salesforce continues to enhance its AI-powered features, keeping pace with advancements in generative and predictive AI. Whether new to the platform or a seasoned user, Salesforce offers innovative, AI-centric solutions to streamline customer relationship management and business operations. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Agentforce - AI's New Role in Sales and Service

Agentforce – AI’s New Role in Sales and Service

From Science Fiction to Reality: AI’s Game-Changing Role in Service and Sales AI for service and sales has reached a critical tipping point, driving rapid innovation. At Dreamforce in San Francisco, hosted by Salesforce we explored how Salesforce clients are leveraging CRM, Data Cloud, and AI to extract real business value from their Salesforce investments. In previous years, AI features branded under “Einstein” had been met with skepticism. These features, such as lead scoring, next-best-action suggestions for service agents, and cross-sell/upsell recommendations, often required substantial quality data in the CRM and knowledge base to be effective. However, customer data was frequently unreliable, with duplicate records and missing information, and the Salesforce knowledge base was underused. Building self-service capabilities with chatbots was also challenging, requiring accurate predictions of customer queries and well-structured decision trees. This year’s Dreamforce revealed a transformative shift. The advancements in AI, especially for customer service and sales, have become exceptionally powerful. Companies now need to take notice of Salesforce’s capabilities, which have expanded significantly. Agentforce – AI’s New Role in Sales and Service Some standout Salesforce features include: At Dreamforce, we participated in a workshop where they built an AI agent capable of responding to customer cases using product sheets and company knowledge within 90 minutes. This experience demonstrated how accessible AI solutions have become, no longer requiring developers or LLM experts to set up. The key challenge lies in mapping external data sources to a unified data model in Data Cloud, but once achieved, the potential for customer service and sales is immense. How AI and Data Integrate to Transform Service and Sales Businesses can harness the following integrated components to build a comprehensive solution: Real-World Success and AI Implementation OpenTable shared a successful example of building an AI agent for its app in just two months, using a small team of four. This was a marked improvement from the company’s previous chatbot projects, highlighting the efficiency of the latest AI tools. Most CEOs of large enterprises are exploring AI strategies, whether by developing their own LLMs or using pre-existing models. However, many of these efforts are siloed, and engineering costs are high, leading to clunky transitions between AI and human agents. Tectonic is well-positioned to help our clients quickly deploy AI-powered solutions that integrate seamlessly with their existing CRM and ERP systems. By leveraging AI agents to streamline customer interactions, enhance sales opportunities, and provide smooth handoffs to human agents, businesses can significantly improve customer experiences and drive growth. Tectonic is ready to help businesses achieve similar success with AI-driven innovation. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Is Agentforce Different?

Is Agentforce Different?

The Salesforce hype machine is in full swing, with product announcements like Chatter, Einstein GPT, and Data Cloud, all positioned as revolutionary tools that promise to transform how we work. Is Agentforce Different? However, it’s often difficult to separate fact from fiction in the world of Salesforce. The cloud giant thrives on staying ahead of technological advancements, which means reinventing itself every year with new releases and updates. You could even say three times per year with the major releases. Why Enterprises Need Multiple Salesforce Orgs Over the past decade, Salesforce product launches have been hit or miss—primarily miss. Offerings like IoT Cloud, Work.com, and NFT Cloud have faded into obscurity. This contrasts sharply with Salesforce’s earlier successes, such as Service Cloud, the AppExchange, Force.com, Salesforce Lightning, and Chatter, which defined its first decade in business. One notable exception is Data Cloud. This product has seen significant success and now serves as the cornerstone of Salesforce’s future AI and data strategy. With Salesforce’s growth slowing quarter over quarter, the company must find new avenues to generate substantial revenue. Artificial Intelligence seems to be their best shot at reclaiming a leadership position in the next technological wave. Is Agentforce Different? While Salesforce has been an AI leader for over a decade, the hype surrounding last year’s Dreamforce announcements didn’t deliver the growth the company was hoping for. The Einstein Copilot Studio—comprising Copilot, Prompt Builder, and Model Builder—hasn’t fully lived up to expectations. This can be attributed to a lack of AI readiness among enterprises, the relatively basic capabilities of large language models (LLMs), and the absence of fully developed use cases. In Salesforce’s keynote, it was revealed that over 82 billion flows are launched weekly, compared to just 122,000 prompts executed. While Flow has been around for years, this stat highlights that the use of AI-powered prompts is still far from mainstream—less than one prompt per Salesforce customer per week, on average. When ChatGPT launched at the end of 2022, many predicted the dawn of a new AI era, expecting a swift and dramatic transformation of the workplace. Two years later, it’s clear that AI’s impact has yet to fully materialize, especially when it comes to influencing global productivity and GDP. However, Salesforce’s latest release feels different. While AI Agents may seem new to many, this concept has been discussed in AI circles for decades. Marc Benioff’s recent statements during Dreamforce reflect a shift in strategy, including a direct critique of Microsoft’s Copilot product, signaling the intensifying AI competition. This year’s marketing strategy around Agentforce feels like it could be the transformative shift we’ve been waiting for. While tools like Salesforce Copilot will continue to evolve, agents capable of handling service cases, answering customer questions, and booking sales meetings instantly promise immediate ROI for organizations. Is the Future of Salesforce in the Hands of Agents? Despite the excitement, many questions remain. Are Salesforce customers ready for agents? Can organizations implement this technology effectively? Is Agentforce a real breakthrough or just another overhyped concept? Agentforce may not be vaporware. Reports suggest that its development was influenced by Salesforce’s acquisition of Airkit.AI, a platform that claims to resolve 90% of customer queries. Salesforce has even set up dedicated launchpads at Dreamforce to help customers start building their own agents. Yet concerns remain, especially regarding Salesforce’s complexity, technical debt, and platform sprawl. These issues, highlighted in this year’s Salesforce developer report, cannot be overlooked. Still, it’s hard to ignore Salesforce’s strategic genius. The platform has matured to the point where it offers nearly every functionality an organization could need, though at times the components feel a bit disconnected. For instance: Salesforce is even hinting at usage-based pricing, with a potential $2 charge per conversation—an innovation that could reshape their pricing model. Will Agents Be Salesforce’s Key to Future Growth? With so many unknowns, only time will tell if agents will be the breakthrough Salesforce needs to regain the momentum of its first two decades. Regardless, agents appear to be central to the future of AI. Leading organizations like Copado are also launching their own agents, signaling that this trend will define the next phase of AI innovation. In today’s macroeconomic environment, where companies are overstretched and workforce demands are high, AI’s ability to streamline operations and improve customer service has never been more critical. Whoever cracks customer service AI first could lead the charge in the inevitable AI spending boom. We’re all waiting to see if Salesforce has truly cracked the AI code. But one thing is certain: the race to dominate AI in customer service has begun. And Salsesforce may be at the forefront. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Agentforce Advances Copilot and Prompt Builder

Agentforce Advances Copilot and Prompt Builder

Agentforce was the highlight of the week in San Francisco during Salesforce’s annual Dreamforce conference—and for good reason! Agentforce Advances Copilot and Prompt Builder and that is truly exciting. Agentforce represents a groundbreaking solution that promises to transform how individuals and organizations interact with their CRM. However, as with any major product announcement, it raises many questions. This was evident during Dreamforce, where admins and developers, eager to dive into Agentforce, had numerous queries. Here’s an in-depth look at what Agentforce is, how it operates, and how organizations can leverage it to automate processes and drive value today. Agentforce Advances Copilot and Prompt Builder Many Dreamforce attendees who anticipated hearing more about Einstein Copilot were surprised by the introduction of Agents just before the event. However, understanding the distinctions between the legacy Einstein Copilot and the new Agentforce is crucial. Agentforce Advances Copilot and Prompt Builder. Agentforce Agents are essentially a rebranding of Copilot Agents but with an essential enhancement: they expand the functionality of Copilot to create autonomous agents capable of tasks such as summarizing or generating content and taking specific actions. Here are some key changes in terminology: Just like Einstein Copilot, Agents use user input—an “utterance”—entered into the Agentforce chat interface. The agent translates this utterance into a series of actions based on configurable instructions, and then executes the plan, providing a response. Understanding Agents: Topics A key difference between Einstein Copilot and Agentforce is the addition of “Topics.” Topics allow for greater flexibility and support a broader range of actions. They organize tasks by business function, helping Agents first determine the appropriate topic and then identify the necessary actions. This topic layer reduces confusion and ensures the correct action is taken. With this structure, Agentforce can support many more custom actions compared to Copilot’s 15-20, significantly expanding capabilities. Understanding Agents: Actions Actions in Agentforce function similarly to those in Einstein Copilot. These are the tasks an agent executes once it has identified the right plan. Out-of-the-box actions are available right away, providing a quick win for organizations looking to implement standard actions like opportunity summarization or sales emails. For more customized use cases, organizations can create bespoke actions using Apex, Flows, Prompts, or Service Catalog items (currently in beta). Understanding Agents: Prompts Whenever an LLM is used, prompts are necessary to provide the right input. Thoughtfully engineered prompts are essential for getting accurate, useful responses from LLMs. This is a key part of leveraging Agent Actions effectively, ensuring better results, reducing errors, and driving productive agent behavior. Prompt Builder plays a crucial role, allowing users to build, test, and refine prompts for Agent Actions, creating a seamless experience between generative AI and Salesforce workflows. How Generative AI and Agentforce Enhance CRM GenAI tools like Agentforce offer exciting enhancements to Salesforce organizations in several ways: However, these benefits are realized only when CRM users adopt and adapt to AI-assisted workflows. Organizations must prioritize change management and training, as most users will need to adjust to this new AI-powered way of working. If your company has already embraced AI, then you are halfway there. If AI hasn’t been introduced to the workforce you need to get started yesterday. Getting Started with Agentforce With all the buzz around Dreamforce, it’s no surprise that many organizations are eager to start using Agentforce. Fortunately, there are immediate opportunities to leverage these tools. The recommended approach is to begin with standard Agent actions, testing out-of-the-box features like opportunity summarization or creating close plans. From there, organizations can make incremental tweaks to customize actions for their specific needs. We have all come to expect that just as quickly as we include agentic ai into our processes and flows, Salesforce will add additional features and capabilities. As teams become more familiar with developing and deploying Agent actions, more complex use cases will become manageable, transforming the traditional point-and-click Salesforce experience into a more intelligent, agent-driven platform. Already I find myself asking, “is this an agent person or an ai-agent”? The day is coming, no doubt, when the question will be reversed. Tectonic’s AI Experts Can Help Interested in learning more about Agentforce or need guidance on getting started? Tectonic specializes in AI and analytics solutions within CRM, helping organizations unlock significant productivity gains through AI-based tools that optimize business processes. We are excited to enable you to enable Agentforce to Advance Copilot and Prompt Builder By Tectonic’s Solutions Architect, Shannan Hearne Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce and Ortoo Integration

Salesforce and Ortoo Integration

Ortoo Launches Smart Actions: A Revolutionary Salesforce-Native App for AI Automation Ortoo, a leading provider of Salesforce productivity solutions, has unveiled its latest innovation, Smart Actions, now available on the Salesforce AppExchange. This groundbreaking Salesforce-native app allows businesses to seamlessly integrate AI automation into their Salesforce workflows, dramatically boosting efficiency and simplifying complex processes with a single click. Salesforce and Ortoo integration for Smart Actions. How do I sync Ortto activities to Salesforce? In your Ortto account, navigate to Data sources > Salesforce > Sync Ortto activities to Salesforce. Choose up to 5 activities. At Sync settings, select whether you wish to sync these Ortto activities as activities and/or as tasks. If you are syncing the Salesforce Task object to Ortto (selected at Salesforce fields): Smart Actions empowers companies to deploy AI and GPT-powered automations across sales, service, and support functions within Salesforce, eliminating the traditionally high costs associated with advanced AI tools. By integrating smoothly into the Salesforce ecosystem, Smart Actions enables businesses to automate manual tasks, personalize communications, and optimize workflows with unparalleled ease. Track and manage email conversations within Salesforce. AI-powered actions to streamline sales workflows. SEAMLESS SALESFORCE INTEGRATION “With Smart Actions, we’re making AI automation accessible to businesses of all sizes,” said Amy Grenham, Head of Marketing at Ortoo. “If you’ve ever built a custom GPT using OpenAI, creating a Smart Action will feel very familiar. Ortoo’s prompt builder allows you to set the context, specify the Salesforce fields to analyze, and determine where the output should go. This simplicity makes it incredibly easy to deploy AI-driven processes and transform operations within Salesforce.” Key Features and Practical Applications Real-World Applications of Smart Actions Get Started with Smart Actions Today Smart Actions is now available on the Salesforce AppExchange. Businesses can start using the app for free, with additional features available through a premium version. SmartActions is a 5 star product on the Salesforce AppExchange. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Einstein Knowledge Edits

Einstein Knowledge Edits

Get Quick Revisions on Knowledge Articles with Einstein Knowledge Edits (Beta) Enhance your Knowledge articles quickly using Einstein generative AI with predefined revision styles. These styles can help improve grammar, conciseness, and readability. You can also customize these styles using the Prompt Builder to tailor the revisions to your business needs. This allows you to specify what information Einstein includes, how the content is formatted, and adjust the voice and tone. Where: This feature is available in Unlimited and Enterprise editions with the Einstein for Service add-on in Lightning Experience. Important: Einstein Knowledge Edits is currently in beta and is subject to Salesforce’s Beta Services Terms or a written Unified Pilot Agreement if executed by the Customer. Participation in this beta service is at the Customer’s discretion. Who: To access Knowledge Edits, you must have the following enabled: Agents also need the Prompt Template User and Einstein Knowledge Creation permission sets. How: To revise a Knowledge article: Quickly and effectively refine your Knowledge articles to meet your business standards with Einstein Knowledge Edits! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Everyone Is Implementing AI

Everyone Is Implementing AI

AI is undoubtedly a generational change in software, with its full trajectory still unpredictable. There is a perceived divide between the “Haves” and “Have Nots.” Companies like OpenAI, Microsoft, and Databricks are seen as understanding AI’s potential, with Nvidia providing the necessary hardware support. Many hot start-ups are Gen AI native, continuing to attract unicorn valuations. Meanwhile, several SaaS leaders appear to be lagging behind. We say, Everyone Is Implementing AI. Marc Benioff stated in their latest quarterly call: “Now, we’re working with thousands of customers to power generative AI use cases with our Einstein Copilot, our prompt builder, our Einstein Studio, all of which went live in the first quarter. And we’ve closed hundreds of copilot deals since this incredible technology has gone GA. And in just the last few months, we’re seeing Einstein Copilot develop higher levels of capability. We are absolutely delighted and cannot be more excited about the success that we’re seeing with our customers with this great new capability.” Everyone Is Implementing AI However, it remains unclear whether simply adding AI to classic B2B SaaS products accelerates growth. Despite significant investments in AI, companies like Salesforce, Asana, and ZoomInfo are growing at less than 10% annually. The main point is that while “AI Washing” might impress some investors, AI must significantly accelerate revenue growth to achieve more than market parity. It is essential to see how AI can add real value and integrate it effectively. But AI alone may not be a growth accelerant. Everyone Is Implementing AI Recent data from Emergence Capital shows that 60% of VC-backed SaaS companies have already released GenAI features, with another 24% planning to do so. Achieving “AI Parity” is crucial, but simply adding GenAI features may not be disruptive in the B2B space. Companies must go further to stand out, despite the 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 Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Einstein Code Generation and Amazon SageMaker

Einstein Code Generation and Amazon SageMaker

Salesforce and the Evolution of AI-Driven CRM Solutions Salesforce, Inc., headquartered in San Francisco, California, is a leading American cloud-based software company specializing in customer relationship management (CRM) software and applications. Their offerings include sales, customer service, marketing automation, e-commerce, analytics, and application development. Salesforce is at the forefront of integrating artificial general intelligence (AGI) into its services, enhancing its flagship SaaS CRM platform with predictive and generative AI capabilities and advanced automation features. Einstein Code Generation and Amazon SageMaker. Salesforce Einstein: Pioneering AI in Business Applications Salesforce Einstein represents a suite of AI technologies embedded within Salesforce’s Customer Success Platform, designed to enhance productivity and client engagement. With over 60 features available across different pricing tiers, Einstein’s capabilities are categorized into machine learning (ML), natural language processing (NLP), computer vision, and automatic speech recognition. These tools empower businesses to deliver personalized and predictive customer experiences across various functions, such as sales and customer service. Key components include out-of-the-box AI features like sales email generation in Sales Cloud and service replies in Service Cloud, along with tools like Copilot, Prompt, and Model Builder within Einstein 1 Studio for custom AI development. The Salesforce Einstein AI Platform Team: Enhancing AI Capabilities The Salesforce Einstein AI Platform team is responsible for the ongoing development and enhancement of Einstein’s AI applications. They focus on advancing large language models (LLMs) to support a wide range of business applications, aiming to provide cutting-edge NLP capabilities. By partnering with leading technology providers and leveraging open-source communities and cloud services like AWS, the team ensures Salesforce customers have access to the latest AI technologies. Optimizing LLM Performance with Amazon SageMaker In early 2023, the Einstein team sought a solution to host CodeGen, Salesforce’s in-house open-source LLM for code understanding and generation. CodeGen enables translation from natural language to programming languages like Python and is particularly tuned for the Apex programming language, integral to Salesforce’s CRM functionality. The team required a hosting solution that could handle a high volume of inference requests and multiple concurrent sessions while meeting strict throughput and latency requirements for their EinsteinGPT for Developers tool, which aids in code generation and review. After evaluating various hosting solutions, the team selected Amazon SageMaker for its robust GPU access, scalability, flexibility, and performance optimization features. SageMaker’s specialized deep learning containers (DLCs), including the Large Model Inference (LMI) containers, provided a comprehensive solution for efficient LLM hosting and deployment. Key features included advanced batching strategies, efficient request routing, and access to high-end GPUs, which significantly enhanced the model’s performance. Key Achievements and Learnings Einstein Code Generation and Amazon SageMaker The integration of SageMaker resulted in a dramatic improvement in the performance of the CodeGen model, boosting throughput by over 6,500% and reducing latency significantly. The use of SageMaker’s tools and resources enabled the team to optimize their models, streamline deployment, and effectively manage resource use, setting a benchmark for future projects. Conclusion and Future Directions Salesforce’s experience with SageMaker highlights the critical importance of leveraging advanced tools and strategies in AI model optimization. The successful collaboration underscores the need for continuous innovation and adaptation in AI technologies, ensuring that Salesforce remains at the cutting edge of CRM solutions. For those interested in deploying their LLMs on SageMaker, Salesforce’s experience serves as a valuable case study, demonstrating the platform’s capabilities in enhancing AI performance and scalability. To begin hosting your own LLMs on SageMaker, consider exploring their detailed guides and resources. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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DPD Salesforce AI Enhancements

DPD Salesforce AI Enhancements

DPD’s AI Integration: Enhancing Customer and Employee Experience DPD has ambitious plans to integrate AI throughout its Salesforce platform, aiming to automate tasks and significantly enhance the experiences of both customers and employees. DPD Salesforce AI Enhancements. Adam Hooper, Head of Central Platforms at DPD, explains that with over 400 million parcels delivered annually, maintaining robust customer relationships is crucial. To this end, DPD leverages a range of Salesforce technologies, including Service Cloud, Sales Cloud, Marketing Cloud, and Mulesoft. AI-Powered Customer Service In Salesforce’s latest update on DPD: Financial and Operational Efficiency Targeted Marketing Spreadsheets to Salesforce At the Salesforce World Tour event in London, Ben Pyne, Salesforce Platform Manager at DPD, elaborated on their current usage and future AI plans. Pyne’s team acts as internal consultants to optimize organizational workflows. As he explains: “My role is essentially to get people off spreadsheets and onto Salesforce!” He noted that about 40 departments and teams within DPD use Salesforce, far beyond the typical Sales and CRM applications. Custom applications within Salesforce personalize and enhance user experiences by focusing on relevant information. Using tools like Prompt Builder, Pyne’s team recently developed a project management app within Salesforce, streamlining tasks like writing acceptance criteria and user stories. Pyne emphasized: “I want our guys to focus on designing and building, less on the admin.” AI Use Cases When considering AI and generative AI, DPD sees significant potential to reduce operational tasks. Pyne highlighted case summarization as an obvious application, given the millions of customer service cases created each year. Rolling Out Generative AI DPD adopts a cautious approach to rolling out new technologies like generative AI. Pyne explained: “It’s starting small, finding the right teams to be able to do it. But fundamentally, starting somewhere and making slow progressions into it to ensure we don’t scare everybody away.” Ensuring Security and Trust Security and trust are paramount for DPD. Pyne noted their robust IT security team scrutinizes every implementation. Fortunately, Salesforce’s security measures, such as data anonymization and preventing LLMs (Large Language Models) from learning from their data, provide peace of mind. Pyne concluded: “We can focus on what we’re good at and not worry about the rest because Salesforce has thought of everything for us.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Adopt a Large Language Model

Adopt a Large Language Model

In 2023, Algo Communications, a Canadian company, faced a significant challenge. With rapid growth on the horizon, the company struggled to train customer service representatives (CSRs) quickly enough to keep pace. To address this, Algo turned to an innovative solution: generative AI. They needed to Adopt a Large Language Model. Algo adopted a large language model (LLM) to accelerate the onboarding of new CSRs. However, to ensure CSRs could accurately and fluently respond to complex customer queries, Algo needed more than a generic, off-the-shelf LLM. These models, typically trained on public internet data, lack the specific business context required for accurate answers. This led Algo to use retrieval-augmented generation, or RAG. Many people have already used generative AI models like OpenAI’s ChatGPT or Google’s Gemini (formerly Bard) for tasks like writing emails or crafting social media posts. However, achieving the best results can be challenging without mastering the art of crafting precise prompts. An AI model is only as effective as the data it’s trained on. For optimal performance, it needs accurate, contextual information rather than generic data. Off-the-shelf LLMs often lack up-to-date, reliable access to your specific data and customer relationships. RAG addresses this by embedding the most current and relevant proprietary data directly into LLM prompts. RAG isn’t limited to structured data like spreadsheets or relational databases. It can retrieve all types of data, including unstructured data such as emails, PDFs, chat logs, and social media posts, enhancing the AI’s output quality. How RAG Works RAG enables companies to retrieve and utilize data from various internal sources for improved AI results. By using your own trusted data, RAG reduces or eliminates hallucinations and incorrect outputs, ensuring responses are relevant and accurate. This process involves a specialized database called a vector database, which stores data in a numerical format suitable for AI and retrieves it when prompted. “RAG can’t do its job without the vector database doing its job,” said Ryan Schellack, Director of AI Product Marketing at Salesforce. “The two go hand in hand. Supporting retrieval-augmented generation means supporting a vector store and a machine-learning search mechanism designed for that data.” RAG, combined with a vector database, significantly enhances LLM outputs. However, users still need to understand the basics of crafting clear prompts. Faster Responses to Complex Questions In December 2023, Algo Communications began testing RAG with a few CSRs using a small sample of about 10% of its product base. They incorporated vast amounts of unstructured data, including chat logs and two years of email history, into their vector database. After about two months, CSRs became comfortable with the tool, leading to a wider rollout. In just two months, Algo’s customer service team improved case resolution times by 67%, allowing them to handle new inquiries more efficiently. “Exploring RAG helped us understand we could integrate much more data,” said Ryan Zoehner, Vice President of Commercial Operations at Algo Communications. “It enabled us to provide detailed, technically savvy responses, enhancing customer confidence.” RAG now touches 60% of Algo’s products and continues to expand. The company is continually adding new chat logs and conversations to the database, further enriching the AI’s contextual understanding. This approach has halved onboarding time, supporting Algo’s rapid growth. “RAG is making us more efficient,” Zoehner said. “It enhances job satisfaction and speeds up onboarding. Unlike other LLM efforts, RAG lets us maintain our brand identity and company ethos.” RAG has also allowed Algo’s CSRs to focus more on personalizing customer interactions. “It allows our team to ensure responses resonate well,” Zoehner said. “This human touch aligns with our brand and ensures quality across all interactions.” Write Better Prompts – Adopt a Large Language Model If you want to learn how to craft effective generative AI prompts or use Salesforce’s Prompt Builder, check out Trailhead, Salesforce’s free online learning platform. Start learning Trail: Get Started with Prompts and Prompt Builder Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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