App Archives - gettectonic.com - Page 46
Create a Service Provider Portal in PSS
23Mar

Create a Service Provider Portal in PSS

Develop a provider portal for certified service providers to manage constituent referral requests, track service delivery, update their information, and collaborate with agencies and constituents effectively. Create a Service Provider Portal in PSS to easily track and manage referral requests. Caseworkers often lack direct insight into the progress of constituents’ benefits and their interactions with service providers, relying on providers to keep them informed. Conversely, providers struggle to maintain updated credentials, contract renewal status, and other information for agencies. To tackle these challenges, establish a portal to aid service providers in managing and monitoring their services while granting agencies and constituents real-time visibility into provider data and processes. This collaborative platform fosters efficient and transparent partnerships. While Public Sector Solutions does not offer a custom template, any Experience Cloud site template, such as the Build Your Own (LWR) template, can be utilized to create the portal for service providers. With the Provider Management for Partner permission set, providers gain access to Provider Management objects and features. Consider the following access-related requirements for the portal: Create a Service Provider Portal in PSS Service providers can leverage the portal in various ways, including: 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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March 23, 2024in Data, Public Sector Solutions, Salesforce, Salesforce Experience Cloud
AI Project Planning by Data
21Mar

AI Project Planning by Data

Starting with Data Step 1: Identify Core Data Stores Begin by listing the primary data sources tied to the business functions you are investigating. While it may be unrealistic to catalog every possible data source within the company, the task becomes manageable by narrowing the focus to specific departments (e.g., customer service, marketing, legal) or broader goals (e.g., “increasing manufacturing efficiency” or “improving customer loyalty and cart value”). Step 2: Align Data with Business Processes For each data set, hypothesize how it might enhance or streamline business workflows. Consider questions like: By linking the data to these business use cases, you start to uncover the potential value of integrating data into key workflows. Step 3: Validate Business Cases with Experts Once you’ve identified how data could be valuable, collaborate with data scientists and subject matter experts (SMEs) to review and refine your hypotheses. Create a formal list of use cases that clearly outline how data, algorithms, and business workflows could come together to add value or automate a process. This ensures a practical approach for leveraging data to drive business outcomes. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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March 21, 2024in Data
Introducing the New Nonprofit Cloud
20Mar

Technology for a Human-Centric Impact: Introducing the New Nonprofit Cloud

In times of disaster or need, it’s not technology that distributes supplies or ensures access to fundamental rights—it’s people. Nonprofits, whether large or small, work alongside individuals, partner organizations, government agencies, healthcare providers, volunteers, and staff to drive community and planetary improvements. From large-scale disaster responses to community food drives, real change and impact come from collaborative efforts, not isolated actions. Introducing the New Nonprofit Cloud for today’s NGOs. Salesforce’s vision for nonprofits has always been to empower impact makers with the best technology. Technology should be a critical enabler that brings people and organizations together, scaling those moments of impact. Breaking Down Barriers for Greater Impact Salesforce aims to simplify operations for the nonprofit sector by breaking down information silos within organizations and among local or global partners. Achieving greater impact collectively requires collaboration with stakeholders, information sharing, and effective data utilization. Salesforce collaborated with partners and nonprofit peers to address four key priorities: Introducing the New Nonprofit Cloud With these priorities in mind, Salesforce has announced a new vision for Nonprofit Cloud—a suite of nonprofit technology solutions built specifically for the sector. For the first time, instead of layering nonprofit applications on top of the platform, Salesforce is building directly into the core, unlocking innovation across all Salesforce industries. The new Nonprofit Cloud aims to address all goals in a single solution. For over two decades, Salesforce has worked with its community and partner ecosystem to deliver purpose-built packages on top of the Salesforce platform. Together, they have built more than 14 software packages, anchored by the Nonprofit Success Pack (NPSP), which is used by thousands of organizations. Salesforce will continue to support existing offerings like NPSP, Nonprofit Cloud Case Management, the Program Management Module, and more. Today, we have the thrill of Introducing the New Nonprofit Cloud However, Salesforce is now offering a new solution to nonprofit organizations with reimagined program management, case management, outcomes, marketing engagement, and fundraising in one package. The next generation of Nonprofit Cloud, available today, focuses on delivering programs and case management, leveraging the full power of the Salesforce platform. Fundraising and outcomes will be integrated into this solution later this year. Faster and Easier Access to Nonprofit Technology Supporters measure organizations by their impact, and the goal is to focus on driving that impact, not piecing together data from different systems. This new approach provides a faster and more unified way to drive impact by consolidating stakeholder experiences from across organizations and partners. The new Nonprofit Cloud unifies programs, fundraising, engagement, and outcomes, giving easier and faster access to innovations from across all of Salesforce. This connection to Salesforce’s portfolio of best-in-class solutions enhances the ability to make data-driven decisions swiftly, focusing on what works and where changes are needed. Greater Cross-Sector Impact – Introducing the New Nonprofit Cloud The new Nonprofit Cloud is designed for whole-person care. By building Nonprofit Cloud directly into the Salesforce platform, it’s easier to adopt technology used in other industries, such as Health & Life Sciences and the Public Sector. This integration reflects how jobs are actually done—working with program participants, their families, governments, healthcare organizations, and other nonprofits to ensure everyone achieves their goals. This fosters better cross-sector engagement and impact for all served. Impact is Driven by Everyone Behind every relationship, person, or program is data. When these data points are combined, they can be learned from, validated, and traced throughout the process. With the reimagined Nonprofit Cloud, Salesforce is building every component with outcomes in mind, partnering with the customer community to determine critical data to capture. This simplifies outcome measurement, reduces the need for heavy customization, and standardizes the process. Introducing the New Nonprofit Cloud Starting with programs and case management, available today, Salesforce will soon add outcomes, engagement, and fundraising, connecting them to all future innovations. The Power of Us Program Salesforce remains committed to giving 1% of equity, product, and employee time back to its communities through the Power of Us program, which grants qualified nonprofit and educational organizations 10 free technology licenses. The new Nonprofit Cloud innovation will be included. Salesforce will also continue to support existing licenses and paid nonprofit offerings, including the Nonprofit Success Pack (NPSP). This new approach for the nonprofit sector has been successfully used by other industries within Salesforce for years. Salesforce is dedicated to continuing investment in best-in-class nonprofit technology to help achieve significant and lasting impact. Connect with Salesforce Ready to implement Salesforce Nonprofit Cloud to streamline operations and amplify impact? Connect with Salesforce experts for more information. 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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March 20, 2024in Salesforce Nonprofit Cloud
Top AI Tools Shaping Business Success
19Mar

Top AI Tools Shaping Business Success

Top AI Tools Shaping Business Success in 2024 In the dynamic world of business, staying ahead means embracing the latest technologies. Artificial Intelligence (AI) is no longer just a buzzword—it’s a transformative force that helps businesses operate more efficiently, make smarter decisions, and enhance customer experiences. As we move through 2024, the AI tool ecosystem is rapidly expanding, offering innovative solutions to automate tasks, gain deep insights, and improve customer engagement. Below, we explore the top AI tools that are shaping the future of business. StoryChief is a comprehensive content marketing platform that simplifies the creation and distribution of content through AI. From ideation to optimization, it leverages machine learning to help businesses generate high-quality, engaging content at scale. Key Features: Pricing: Plans start with a free tier, with paid options ranging from $40 to $500 per month. Developed by OpenAI, ChatGPT is a versatile language model capable of generating human-like text. It excels in content creation, customer support, and data analysis. Key Use Cases: Pricing: API access with usage-based pricing. Perplexity AI is an advanced search engine that provides accurate, summarized answers to complex queries using natural language processing (NLP). Key Features: Pricing: Free version available, with Pro version at $20/month offering enhanced features. Zapier connects over 5,000 apps, enabling automation of repetitive tasks across your tech stack with AI-powered tools that simplify complex automations. Key Features: Pricing: Free plan available for up to 100 tasks per month; paid plans start at $19.99/month. Grammarly is an AI-driven writing assistant that enhances the quality of written communication, ensuring clarity, conciseness, and error-free content. Key Features: Pricing: Free version available; Premium plans start at $12/month for individuals and $25/user/month for businesses. Typeframes simplifies video creation with AI, turning scripts or images into professional-quality videos with animations, transitions, and voiceovers. Key Features: Pricing: Plans start at $29/month, with higher-tier options available. Chatbase enables businesses to build intelligent chatbots and virtual assistants that handle a wide range of customer service inquiries. Key Features: Pricing: Free plan available with limited message credits; paid plans start at $19/month. Secta is an AI-powered headshot generator that creates professional-quality headshots from user-submitted photos, ideal for businesses needing polished profile pictures. Key Features: Pricing: Pay-as-you-go at $49 per headshot session. Voicenotes is an AI-driven transcription tool that converts voice memos into concise summaries and action items, perfect for capturing important information efficiently. Key Features: Pricing: Free plan available; paid plans start at $10/month, with lifetime payment options. Notion AI enhances the popular Notion productivity platform with AI-powered writing assistance, content summarization, and database management. Key Features: Pricing: Available as an add-on at $10 per user per month, with discounts for annual plans. Choosing the Right AI Tools for Your Business Selecting the right AI tools involves considering several factors: By evaluating these aspects, you can effectively leverage AI to enhance efficiency, drive growth, and maintain a competitive edge in 2024. 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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March 19, 2024in Salesforce
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 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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March 18, 2024in Mulesoft, 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 Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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March 16, 2024in Generative AI, Salesforce Einstein
Prompt Decomposition
15Mar

Prompt Decomposition

Optimizing Generative AI: Overcoming Adoption Barriers Through Prompt Decomposition Understand and Control Every Element of Your Workload Prompt Decomposition decompose the task into steps that focus on age date and interest allowing for accurate recommendations based on predefined test cases. Challenges in Scaling Generative AI As Generative AI Specialist at AWS, Iweve worked with over 50 customers in the last 18 months, encountering numerous generative AI proof of concepts (PoCs). Many teams struggle to move beyond the PoC stage due to several common challenges: Solution: Prompt Decomposition Prompt decomposition offers a solution to these common issues by breaking down complex prompts into manageable parts. While other techniques exist, prompt decomposition stands out for its ability to address these blockers effectively. Does Prompt Decomposition Really Work? Yes, it does. This technique has proven effective in unlocking scalability for some of AWS’s largest clients across various sectors. In this blog post, I will share code examples for two use cases that illustrate how prompt decomposition can improve accuracy and reduce latency. Each example will demonstrate changes in cost, latency, and accuracy before and after applying prompt decomposition. Example Results What is Prompt Decomposition? Prompt decomposition involves breaking down a complex prompt into smaller, more manageable components. This approach simplifies large tasks into sequential, manageable steps, improving execution efficiency. Example: Summer Camp Recommendation System Consider a system recommending summer camps based on a child’s age, desired camp date, and interests. The process can be decomposed into three steps: Parallel Execution For particularly lengthy prompts, decomposing them into parallel tasks can significantly reduce execution time. For example, a prompt initially taking 43 seconds can be broken into three parallel parts, reducing the total execution time to under 10 seconds without sacrificing accuracy. Conclusion Prompt decomposition is a powerful technique to overcome common challenges in generative AI projects. By breaking down complex tasks, teams can improve accuracy, manage costs and latency, and gain better control and metrics, leading to more scalable and reliable solutions. Ready to Build? For those ready to dive in, full code examples are available in the GitHub repository linked below. The repository includes a Jupyter Notebook (Prompt_Decomposition.ipynb) with two examples: one focused on accuracy and the other on latency. An updated evaluation function for multithreaded calls to Amazon Bedrock is also included. Starting with Evaluation Automated evaluation is crucial for assessing generative AI performance. Begin with a gold standard set of input/output pairs created by humans to serve as a benchmark. Avoid using generative AI to create this set, as it may introduce inaccuracies. The evaluation function compares the correct and generated answers, scoring them similarly to how a teacher would grade student work. Here’s a sample evaluation prompt: pythonCopy codetest_prompt_template_system = “””You are a detail-oriented teacher. You are grading an exam, looking at a correct answer and a student submitted answer. Your goal is to score the student answer based on how close it is to the correct answer. This is a pass/fail test. If the two answers are basically the same, the score should be 100. Minor things like punctuation, capitalization, or spelling should not impact the score. If the two answers are different, then the score should be 0. Please use your score in a ‘score’ XML tag, and any reasoning in a ‘reason’ XML tag. “”” Task-Based Decomposition Example For a summer camp recommendation system, we decompose the task into steps that focus on age, date, and interests, allowing for accurate recommendations based on predefined test cases. Volume-Based Decomposition Use Case To handle long prompts efficiently, such as analyzing an entire novel, we break the task into smaller, parallel parts, significantly improving execution time and accuracy. Prompt Decomposition Creating a flowchart for your task and selecting the best tools for each step can greatly enhance your generative AI workflows. Explore the full code in the GitHub repository, and feel free to comment with questions or share your own experiences. Let’s build something amazing by breaking it down into manageable pieces! 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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March 15, 2024in Salesforce
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 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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March 14, 2024in AI Tools, Data, Generative AI, Salesforce, Salesforce Einstein
Customized Conversational AI Assistant
11Mar

Customized Conversational AI Assistant

Create and Customize a Conversational AI Assistant for CRM Einstein Copilot is your all-in-one CRM AI assistant, seamlessly integrated into every Salesforce application. It empowers teams to accelerate tasks with intelligent actions, deploy conversational AI with built-in trust, and easily scale a unified copilot across your organization. Customized Conversational AI Assistant. Einstein 1 Studio Customize and Enhance AI for CRM:Einstein 1 Studio allows you to tailor Einstein Copilot to your specific business needs. Configure actions, prompts, and models to create a personalized AI experience. Users can interact with the AI using natural language, making task execution more intuitive and efficient. Copilot Builder Expand Einstein Copilot with Advanced Features:Enhance Einstein Copilot by integrating actions with familiar Salesforce platform features like Flows, Apex code, and Mulesoft APIs. Convert workflows into copilot actions and test these interactions within a user-friendly interface, enabling you to monitor and refine your copilot’s performance. Prompt Builder Accelerate Employee Task Completion:Design prompt templates that quickly summarize and generate content, helping employees complete tasks faster. Create prompts that draw from CRM data, Data Cloud, and external sources to make every business task more relevant. Develop prompts once and deploy them across Einstein Copilot, Lightning pages, and flows. Model Builder Integrate and Manage AI Models:Incorporate your predictive AI models and large language models (LLMs) within Salesforce through the Einstein Trust Layer. Utilize no-code ML models in Data Cloud, and manage all your AI models from a centralized control platform, ensuring seamless operation and integration. Deploy Trustworthy AI Leverage Generative AI with Built-In Safeguards:Einstein Copilot is designed to ensure the privacy and security of your data, while improving result accuracy and promoting responsible AI use across your organization. Built directly into the Salesforce Platform, the Einstein Trust Layer offers top-tier features and safeguards to ensure your AI deployments are trustworthy. “The combination of AI, data, and CRM allows us to help busy parents solve the ‘what’s for dinner’ dilemma with personalized recipe recommendations their family will love.”— Heather Conneran, Director, Brand Experience Platforms, General Mills 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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March 11, 2024in Data, Generative AI, Mulesoft, Salesforce
Leverage AI and Machine Learning in Your Data Warehouse
08Mar

Exploring Machine Learning with Salesforce

Machine Learning (ML) falls into three main categories: Supervised Learning, Unsupervised Learning, and Reinforcement Learning. Let’s dive into some issues and considerations that might leave you wondering if it’s even worth starting! Not embracing what Professor Stuart Russell called “the biggest event in human history” may be short-sighted. Don’t worry, Salesforce can help. Salesforce and Machine Learning Salesforce has a 20-year history of making complex technologies business-friendly. This extends to Machine Learning, integrating ML capabilities throughout the Salesforce Customer 360 suite, which includes solutions for Marketing, Commerce, Sales, Service, and Analytics, among others. Machine Learning in Action with Salesforce Marketing Imagine you’re in a marketing role. You want to predict the likelihood that a customer will engage with your campaigns to maximize effectiveness. Supervised Learning can help here by predicting subscriber engagement (opens, click-throughs, conversions) using historical data (90 days of engagement metrics). For example, using predictive Engagement Scoring, a Salesforce customer in the travel industry achieved a 66% drop in unsubscribe rates and a 13% revenue increase. You also want to ensure prospective customers can quickly find relevant products. Unsupervised Learning can personalize product assortments throughout the shopper journey by analyzing buying patterns, site browsing tendencies, and relationships between search terms and products. Using AI-powered Predictive Sort, businesses have seen a 9.1% increase in revenue per visitor and a 3.8% increase in conversion rates. Sales For sales teams handling many opportunities, predicting the quality of each Opportunity can help prioritize efforts. Supervised Learning, using historical data of at least 200 Closed/Won and 200 Closed/Lost Opportunities, can provide a prioritized list of Opportunities to maximize revenue potential. A large Salesforce customer in the consumer goods sector increased win rates by 48% by focusing on the best Opportunities. Service Post-sale customer support is crucial. Service agents need to address challenging cases efficiently. Supervised Learning can recommend articles to resolve current cases based on historical data from at least 1000 cases with knowledge base articles. A large electronics company using Salesforce AI-powered solutions saved 5 hours per agent per week, enhancing productivity. Simplifying Complex Technology Salesforce’s rich history of making complex technology accessible allows businesses to realize ML benefits without needing specialized knowledge. Traditional ML involves multiple steps like data collection, transformation, sampling, feature selection, model selection, score calibration, and integrating results. Salesforce simplifies this with a customizable data model, automated feature engineering, and automatic model building and selection. For example, in model selection, Salesforce runs a “model tournament” to choose the best model with varying hyper-parameters, ensuring the most accurate model is selected without requiring user intervention. Conclusion Salesforce abstracts the complexity of ML behind user-friendly interfaces, making it easier for businesses to leverage powerful technology. Whether it’s predicting customer engagement, personalizing shopping experiences, prioritizing sales opportunities, or enhancing customer support, Salesforce’s ML capabilities can drive significant business value. Discover more about how Salesforce can transform your approach to Machine Learning and help you achieve your business goals. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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March 8, 2024in Data, Technology
Workflow Rules & Process Builder End of Support
07Mar

Workflow Rules And Process Builder End of Support

Publish Date: Mar 5, 2024 Description Salesforce will no longer be supporting Workflow Rules and Process Builder on December 31, 2025, and we recommend that you migrate your automation to Flow Builder by that time. Workflow Rules & Process Builder End of Support You’re also probably wondering why we’re retiring Workflow Rules and Process Builder. Salesforce wants to focus development on a modern, extensible, low-code automation solution in Flow Builder, which led us to retire the previous features. What does this change mean for me? If you have active Workflow Rules or Process Builder processes running after 2025, they will no longer receive customer support or bug fixes. What action can I take? We recommend implementing a plan to migrate any active rules or processes to Flow Builder before the deadline. Depending on the complexity of your org, this migration may take a significant amount of time and testing, so we recommend starting now. To assist in the migration process, we have a Migrate to Flow tool and extensive support resources available. What happens if I don’t take action? After December 31, 2025, Workflow Rules and Process Builder may continue to function and execute existing automation, but customer support will not be available, and bugs will not be fixed. How do I identify affected users? You can identify whether you have active workflow rules by going to Setup | Process Automation | Workflow Rules and sorting the Active column for checkmarks. You can identify whether you have active Process Builder processes by going to Setup | Process Automation | Process Builder and sorting the Status column for Active. If you have more questions, open a case with support via Salesforce Help. To view all current and past retirements, see Salesforce Product & Feature Retirements. To read about the Salesforce approach to retirements, read our Product & Feature Retirement Philosophy. 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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March 7, 2024in Salesforce
AI and the Role of Healthcare CIOs
07Mar

AI and the Role of Healthcare CIOs

Healthcare leaders see significant potential in data analytics and AI technology to transform the industry over the next five years, according to a new market research report from Arcadia and The Harris Poll. AI and the Role of Healthcare CIOs The report, titled “The Healthcare CIO’s Role in the Age of AI,” examines AI’s impact on the healthcare sector and how decision-makers are preparing to leverage the technology. Notably, 96% of healthcare leaders surveyed believe that adopting AI effectively will provide a competitive edge both now and in the future. While only a third see AI as essential today, 73% expect it to become critical within five years. How Health Systems Are Using AI Around 63% of respondents revealed that their organizations use AI to analyze large patient data sets to identify trends and guide population health management efforts. Another 58% are using AI to analyze individual patient data to identify opportunities for improving health outcomes. Close to half of the leaders indicated that AI is being used to optimize electronic health records (EHR) management and analysis. These trends align with the findings of the recent “Top of Mind for Top Health Systems” survey, conducted by the University of Pittsburgh Medical Center’s Center for Connected Medicine (CCM) in collaboration with KLAS, which identified AI as the most exciting emerging technology in healthcare with transformative potential for both administration and care delivery. The excitement surrounding healthcare AI largely stems from its ability to break down data silos and tap into the wealth of clinical data that healthcare organizations already collect. “Healthcare leaders are thoughtfully preparing to harness the full value of AI in care delivery reform,” said Aneesh Chopra, Arcadia’s chief strategy officer. “As safe, secure data sharing scales, technology leaders prioritize data platforms that organize fragmented patient records into clinically relevant insights at every stage of the patient journey.” A quest for a 360 degree patient view abounds. Using AI to Support Strategic Priorities The Arcadia survey emphasized the importance of using analytics to improve patient care, with 83% of leaders believing that harnessing data will help healthcare organizations remain competitive and resilient while overcoming digital transformation and financial challenges. Eighty-four percent of respondents cited technology as a current priority, with 44% focusing on an enterprise-wide approach to data analytics, 41% prioritizing AI-driven decision-making, and 32% working to simplify technical ecosystems. These efforts are viewed as crucial to advancing other strategic goals, with 40% of leaders prioritizing the patient experience, 35% aiming to improve outcomes, and 29% focusing on patient engagement. Although healthcare leaders view AI adoption positively for strategic advancements, hurdles remain. While 96% of respondents are confident in adopting AI, many feel pressured to move quickly. When asked about the sources of this pressure, 82% cited data and analytics teams, 78% pointed to IT and tech teams, and 73% mentioned executives. However, successfully implementing AI requires talent and resources that some organizations lack. About 40% of leaders identified a lack of talent as a significant barrier to AI adoption, signaling the need for IT and analytics teams to acquire new skill sets. Seventy-one percent of IT leaders reported a growing demand for data-driven decision-making skills, while two-thirds pointed to a rising need for expertise in data analysis, machine learning, and systems integration. Additionally, nearly 60% mentioned the need for roles that focus on training and support for healthcare staff. The Evolving Role of CIOs CIOs and other healthcare leaders are seeing their roles evolve as AI and data become more integrated into healthcare operations. Eighty-seven percent of respondents see themselves as strategy influencers, actively involved in setting and executing AI strategies, while only 13% view themselves as purely focused on implementation. Despite these evolving roles, many CIOs feel constrained by daily operations. Fifty-eight percent reported being primarily focused on tactical execution rather than developing long-term AI strategies, although they believe they should spend 75% of their time on strategic planning to be most effective. Part of these strategies will likely focus on improving communication and workforce readiness. Three out of four leaders cited a lack of effective communication between IT teams and clinical staff as a barrier to leveraging new technologies, and two out of five noted that clinical staff are not fully equipped to make the best use of data analytics. “CIOs and their teams are setting the stage for an AI-powered revolution in patient care and healthcare operations,” said Michael Meucci, Arcadia’s president and CEO. “Our findings highlight a strong consensus that a solid data foundation is necessary to realize the future of AI in healthcare. At the same time, the human workforce, with evolving talent and skills, will shape the real-world impact of AI in healthcare.“ Content updated August 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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March 7, 2024in Generative AI, Salesforce Development Services, Salesforce Health and Life Sciences Solutions
Tectonic at a Glance
04Mar

AI Product Management Tools

Embracing AI in Product Management: Your New Best Friend, Not a Replacement-Original published by https://zedaio.medium.com/ Amid the lively debates about AI taking over product management roles, let’s set the record straight: AI is here as an ally, not a replacement. It’s about leveraging AI to amplify our capabilities, streamline mundane tasks, and make room for the creative and strategic aspects of product management. AI Product Management Tools. Here are seven AI tools that will automate your daily routines, offering support that transforms the way you manage products. Ready to upgrade your product management game with AI by your side? Let’s dive in! 1. Zeda.io Zeda.io is one of the best AI tools for product managers. It offers a complete suite of features that help you in feedback management, strategic planning, and closing the loop. It is a perfect tool if you are striving to balance your customer needs and business goals. With integrations like Slack, Gong, Teams, Salesforce, and more, you can gather and manage customer feedback effortlessly. Its unique AI technology generates valuable, actionable insights by categorizing all the feedback, helping you uncover pressing customer issues and decide what to build next. Key Features: 2. ChatGPT An obvious choice, ChatGPT can automate many of your tasks. It helps make sense of vague product user feedback, create PRDs, release notes, and other documents. The key is to use the right prompts and GPT plugins tailored for product managers. Key Features: 3. Notion AI Notion is a cloud-based productivity and collaboration tool that provides various organizational tools, including task management, project tracking, to-do lists, bookmarking, and more. Notion’s AI can assist product managers in several ways. Key Features: 4. Uizard Uizard is a user interface design tool that uses AI to quickly and efficiently create wireframes, mockups, and prototypes in minutes. The tool’s advanced deep-learning algorithms analyze images provided by product teams and managers to create design themes. Key Features: 5. ClickUp ClickUp is a cloud-based tool that helps teams manage their work effectively, offering features like task management, time tracking, file sharing, and communication tools. ClickUp is highly customizable and offers multiple AI tools that integrate seamlessly into workflows. Key Features: 6. Delibr Delibr is an excellent tool for AI product teams to collaborate effectively during the feature refinement process. It helps capture, synthesize, and organize feedback from diverse sources, enabling informed decision-making and creating high-quality documentation. Key Features: 7. Fireflies.ai Fireflies.ai enhances meeting productivity by transcribing, summarizing, and analyzing voice conversations. It integrates with major video-conferencing platforms and offers various ways to capture meetings, including a Chrome extension and direct uploads. Key Features: AI Product Management Tools Embracing AI in product management doesn’t mean diminishing the value of human insight; it’s about enhancing our capabilities and efficiency. The seven AI tools outlined here offer a glimpse into a future where technology and creativity intersect, empowering product managers to achieve more in less time. By integrating suitable tools into your workflow, you can focus on innovation and strategy, ensuring your products not only meet but exceed user expectations. Let AI be your ally to achieve greater heights and product success. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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March 4, 2024in AI Tools, Data, Google, Salesforce, Salesforce Einstein, Technology
03Mar

Train Your Own SORA Model

Unveiling the Vision Transformer: A Leap in Video Generation The closest open-source model to SORA is Latte, which uses the same Vision Transformer architecture. So, what makes the Vision Transformer so outstanding, and how does it differ from previous methods? You can Train Your Own SORA Model. Latte hasn’t open-sourced its text-to-video training code. We’ve replicated this code from the paper and made it available for anyone to use in training their own SORA alternative model. Let’s discuss how effective our training was. From 3D U-Net to Vision Transformer Image generation has advanced significantly, with the U-Net model structure being the most commonly used: If you’re confused about the network structures, remember the key principle of deep learning: “Just Add More Layers!” Vision Transformer: A Game Changer In 3D U-Net, the transformer can only function within the U-Net, limiting its view. The Vision Transformer, however, enables transformers to globally manage video generation. Training Your Open-Source SORA Alternative with Latte Latte uses the video slicing sequence and Vision Transformer method discussed. While Latte hasn’t open-sourced its text-to-video model training code, we’ve replicated it here: GitHub Repo. Training involves three steps: For more details, see the GitHub repo. They’ve also made improvements to the training process: Model Performance The official Latte video shows impressive performance, especially in handling significant motion. However, our own tests indicate that while Latte performs well, it isn’t the top-performing model. Other open-source models have shown better performance. We will continue to share information on models with better performance, so stay tuned to Tectonic’s Insights. Hardware Requirements Due to its large scale, training Latte requires an A100 or H100 with 80GB of memory. 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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March 3, 2024in Salesforce

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