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Data Cloud and Genpact
07Aug

Data Cloud and Genpact

Genpact (NYSE: G), a global professional services and solutions firm delivering outcomes that shape the future, announced today its integration with Salesforce Data Cloud to offer AI-driven industry-specific cloud solutions to transform operations and drive competitive advantages for enterprises. Genpact’s integration with Data Cloud will solve issues associated with disconnected and unstructured data, including poor quality, accessibility, and scalability. By combining Genpact’s deep industry knowledge in consumer goods, life sciences, manufacturing, banking, and insurance, with Data Cloud, businesses can improve decision-making, optimize operations, and drive growth. “To navigate an increasingly complex business environment, business leaders must unlock the full potential of their data assets – but they can only do so if they have a more holistic view,” said Riju Vashisht, Chief Growth Officer, Genpact. “Our partnership with Salesforce combines our data, technology, and AI expertise and a global talent pool with the Salesforce Data Cloud, helping businesses break down data silos, gain real-time insights, and deliver personalized experiences at scale.” Data Cloud offers a 360-degree view of the customer every team can act on by seamlessly connecting, unifying, and activating data that lives in silos across an organization. This allows Genpact to better enable automation, analytics, and personalized engagement. Genpact has also launched a comprehensive training program for its employees on Salesforce’s Einstein AI and Data Cloud platforms to enhance skills and boost innovation to stay ahead in the AI landscape.  “Data Cloud is the platform powering organizations’ data and AI driven engagement. Data Cloud seamlessly harmonizes and unifies structured and unstructured data to deliver integrated experiences,” said Rahul Auradkar, EVP and GM, Unified Data Services and Einstein, Salesforce. “The AI revolution is about data, Data Cloud in concert with Salesforce Einstein 1 platform drives predictive and generative AI, automation, and analytics for customer engagement.” Genpact’s collaboration with Salesforce underscores the company’s commitment to delivering high-quality solutions and achieving client satisfaction within the Salesforce ecosystem. Visit here for more information about Genpact and Salesforce. About Genpact Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose – the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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August 7, 2024in Einstein 1 Platform, Generative AI, Salesforce Data Cloud, Salesforce Einstein
Impact of EHR Adoption
07Aug

Connected Care Technology

How Connected Care Technology Can Transform the Provider Experience Northwell Health is leveraging advanced connected care technologies, including AI, to alleviate administrative burdens and foster meaningful interactions between providers and patients. While healthcare technology has revolutionized traditional care delivery models, it has also inadvertently created barriers, increasing the administrative workload and distancing providers from their patients. Dr. Michael Oppenheim, Senior Vice President of Clinical Digital Solutions at Northwell Health, highlighted this challenge during the Connected Health 2024 virtual summit, using a poignant illustration published a decade ago in the Journal of the American Medical Association. The image portrays a physician focused on a computer with their back to a patient and family, emphasizing how technology can inadvertently shift attention away from patient care. Reimagining Technology to Enhance Provider-Patient Connections To prevent technology from undermining the patient-provider relationship, healthcare organizations must reduce the administrative burden and enhance connectivity between patients and care teams. Northwell Health exemplifies this approach by implementing innovative solutions aimed at improving access, efficiency, and communication. 1. Expanding Access Without Overloading Providers Connected healthcare technologies can dramatically improve patient access but may strain clinicians managing large patient panels. Dr. Oppenheim illustrated how physicians often need to review extensive patient histories for every interaction, consuming valuable time. Northwell Health addresses this challenge by employing mapping tools, propensity analyses, and matching algorithms to align patients with the most appropriate providers. By connecting patients to specialists who best meet their needs, providers can maximize their time and expertise while ensuring better patient outcomes. 2. Leveraging Generative AI for Chart Summarization Generative AI is proving transformative in managing the immense data volumes clinicians face. AI-driven tools help summarize patient records, extracting clinically relevant details tailored to the provider’s specialty. For instance, in a pilot at Northwell Health, AI successfully summarized complex hospitalizations, capturing the critical elements of care transitions. This “just right” approach ensures providers receive actionable insights without unnecessary data overload. Additionally, ambient listening tools are being used to document clinical consultations seamlessly. By automatically summarizing interactions into structured notes, physicians can focus entirely on their patients during visits, improving care quality while reducing after-hours charting. 3. Streamlining Team-Based Care Effective care delivery often involves a multidisciplinary team, including primary physicians, specialists, nurses, and social workers. Coordinating communication across these groups has historically been challenging. Northwell Health is addressing this issue by adopting EMR systems with integrated team chat functionalities, enabling real-time collaboration among care teams. These tools facilitate better care planning and communication, ensuring patients receive coordinated and consistent treatment. Dr. Oppenheim emphasized the importance of not only uniting clinicians in decision-making but also involving patients in discussions. By presenting clear, viable options, providers can enhance patient engagement and shared decision-making. The Path Forward: Balancing Technology with Provider Needs As healthcare continues its digital transformation, connected care technologies must prioritize clinician satisfaction alongside patient outcomes. Tools that simplify workflows, enhance communication, and reduce administrative burdens are crucial for fostering provider buy-in and ensuring the success of health IT initiatives. Northwell Health’s efforts demonstrate how thoughtfully implemented technologies can empower clinicians, strengthen patient relationships, and create a truly connected healthcare experience. Tectonic is here to help your facility plan. Content updated November 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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August 7, 2024in Data, Generative AI, Life Sciences Cloud, Salesforce Health and Life Sciences Solutions, Technology
Box Acquires Alphamoon
07Aug

Box Acquires Alphamoon

Box Inc. has acquired Alphamoon to enhance its intelligent document processing (IDP) capabilities and its enterprise knowledge management AI platform. Now that Box acquires Alphamoon, it will imr improves IDP. Box Acquires Alphamoon IDP goes beyond traditional optical character recognition (OCR) by applying AI to scanned paper documents and unstructured PDFs. While AI technologies like natural language processing (NLP), workflow automation, and document structure recognition have been around for some time, Alphamoon introduces generative AI (GenAI) into the mix, providing advanced capabilities. According to Rand Wacker, Vice President of AI Product Strategy at Box, the integration of GenAI helps not only with summarizing and extracting content from documents but also with recognizing document structures and categorizing them. GenAI works alongside existing OCR and NLP tools, making the digital conversion of paper documents more accurate. Box Acquires Alphamoon – Not LLM Although Box hasn’t acquired a large language model (LLM) outright, it has gained a toolkit that will enhance its Box AI platform. Box AI already uses retrieval-augmented generation to combine a user’s content with external LLMs, ensuring data security while training Box AI to better recognize and categorize documents. Alphamoon’s technology will further refine this process, enabling administrators to create tools more efficiently within the Box ecosystem. “For example, if Alphamoon’s OCR misreads or misextracts something, the system can adjust that specific part and feed it back into the LLM,” Wacker explained. “This approach is powered by an LLM, but it’s specifically trained to understand the documents it encounters, rather than relying on generic content from the internet.” Previewing an upcoming report from Deep Analysis, founder Alan Pelz-Sharpe shared that a survey of 500 enterprises across various industries, including financial services, manufacturing, healthcare, and government, revealed that 53% of enterprise documents still exist on paper. This highlights the need for Box users to have more precise tools to digitize contracts, letters, invoices, faxes, and other paper-based documents. Alphamoon’s generative AI-driven IDP solution allows for human oversight to ensure that attributes are correctly imported from the original documents. Pelz-Sharpe noted that IDP is challenging, but AI has made significant advancements, especially in handling imperfections like crumpled paper, coffee stains, and handwriting. He added that this acquisition addresses a critical gap for Box, which previously relied on partners for these capabilities. Box Buys Alphamoon – Integration Box plans to integrate Alphamoon’s tools into its platform later this year, with deeper integrations expected next year. These will include no-code app-building capabilities related to another acquisition, Crooze, as well as Box Relay’s forms and document generation tools. 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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August 7, 2024in Generative AI
Salesforce Query Builder
07Aug

Salesforce Query Builder

Salesforce Query Builder Effortlessly Build SOQL Queries for Salesforce Objects with Salesforce Query Builder. The Salesforce Query Builder is a powerful Chrome extension that simplifies the creation of SOQL (Salesforce Object Query Language) queries for administrators, developers, and power users. This tool addresses the common challenge of building complex queries directly within your Salesforce environment, eliminating the need for external tools. Key Features and Benefits Seamless Integration: The Query Builder works directly within your Salesforce tabs, streamlining your workflow by removing the need to switch between apps or browser windows. This integration ensures better productivity without disruption. User-Friendly Interface: Its intuitive design makes query building easy for users at any skill level. A step-by-step process walks you through selecting objects, fields, and applying filters, reducing the complexities of SOQL syntax. Dynamic Object and Field Selection: The extension automatically fetches and displays available Salesforce objects and fields, saving time and minimizing errors by using up-to-date schema information. Real-Time Query Generation: As you choose objects, fields, and filters, the extension generates the SOQL query in real-time. This live feedback helps you understand the structure of the query, allowing for quick adjustments. Secure Authentication: Using your existing Salesforce session, the Query Builder ensures your credentials remain secure. It doesn’t store or transmit sensitive information, maintaining the integrity of your data. Flexible Filtering: Easily add WHERE clauses to filter data based on specific criteria, making it simple to focus on the data subsets you need. Copy to Clipboard: With one click, copy the generated SOQL query to your clipboard for easy use in other tools, development environments, or for sharing with teammates. Field Search: For objects with many fields, the search function helps you quickly locate the fields you need, reducing time spent scrolling. Lightweight and Fast: As a browser extension, the Query Builder is lightweight, requiring no installation on your Salesforce instance, ensuring fast performance without impacting your org. Cross-Domain Support: The tool supports multiple Salesforce domains (salesforce.com, force.com, cloudforce.com), providing a consistent experience across different environments. Why You Should Install It Time-Saving: The Query Builder dramatically reduces the time spent constructing SOQL queries, especially for complex objects or unfamiliar schemas. Error Reduction: By providing a visual interface, the tool minimizes syntax errors that can occur when manually writing SOQL queries. Learning Tool: Ideal for those new to SOQL, the Query Builder helps users understand query structure and best practices through its interactive design. Increased Productivity: With seamless Salesforce integration, you can generate queries quickly without disrupting your workflow. Accessibility: The tool empowers users who may not be comfortable writing SOQL manually, making advanced querying capabilities accessible to a wider range of Salesforce users. Consistency: It encourages consistent query-building practices across teams, making collaboration and sharing of queries easier. No Setup Required: As a browser extension, it requires no changes to your Salesforce org, making it perfect for admins or developers working across multiple orgs or with limited customization permissions. By installing the Salesforce Query Builder, you gain a valuable tool for your daily Salesforce tasks. Whether you’re a developer needing to prototype queries, an admin exploring data relationships, or a business analyst needing custom views, this tool simplifies interacting with your Salesforce data. With its combination of ease of use, security, and powerful features, it’s an essential addition to any Salesforce professional’s toolkit. 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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August 7, 2024in Data, Salesforce
Understanding AI Agents
06Aug

Understanding AI Agents

Understanding AI Agents: A Comprehensive Guide Artificial Intelligence (AI) has come a long way, offering systems that automate tasks and provide intelligent, responsive solutions. One key concept within AI is the AI agent—an autonomous system capable of perceiving its environment and taking actions to achieve specific goals. This guide explores AI agents, their types, working mechanisms, and how to build them using platforms like Microsoft Autogen and Google Vertex AI Agent Builder. It also highlights how companies like LeewayHertz and Markovate can assist in the development of AI agents. What is an AI Agent? AI agents are systems designed to interact with their environment autonomously. They process inputs, make decisions, and execute actions based on predefined rules or learned experiences. These agents range from simple rule-based systems to complex machine learning models that adapt over time. Types of AI Agents AI agents can be classified based on complexity and functionality: How AI Agents Work The working mechanism of an AI agent involves four key components: Architectural Blocks of an Autonomous AI Agent An autonomous AI agent typically includes: Building an AI Agent: The Basics Building an AI agent involves several essential steps: Microsoft Autogen: A Platform Overview Microsoft Autogen is a powerful tool for building AI agents, offering a range of features that simplify the development, training, and deployment process. Its user-friendly interface allows developers to create custom agents quickly. Key Steps to Building AI Agents with Autogen: Benefits of Autogen: Vertex AI Agent Builder: Enabling No-Code AI Development Google’s Vertex AI Agent Builder simplifies AI agent development through a no-code platform, making it accessible to users without extensive programming experience. Its drag-and-drop functionality allows for quick and efficient AI agent creation. Key Features of Vertex AI Agent Builder: Conclusion AI agents play a critical role in automating decision-making and performing tasks independently. Platforms like Microsoft Autogen and Google Vertex AI Agent Builder make the development of these agents more accessible, providing powerful tools for both novice and experienced developers. By leveraging these technologies and partnering with companies like LeewayHertz and Markovate, businesses can build custom AI agents that enhance automation, decision-making, and operational efficiency. Whether you’re starting from scratch or looking to integrate AI capabilities into your existing systems, the right tools can make the process seamless and effective. How do you think these tools stack up next to Salesforce AI Agents? Comment below. Content updated October 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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August 6, 2024in AI Tools, Artificial Intelligence, Data, Google
Read AI Salesforce Integration
06Aug

Read AI Salesforce Integration

Last month, Read AI announced the launch of its integration with HubSpot, and today the company continues its momentum in the CRM space by announcing support for 1-click connections to Salesforce. Salesforce, the leading name in CRM software, is widely adopted across virtually every industry. Read AI users can now sync their Meeting Reports directly to corresponding records within their Salesforce instance, either automatically or manually. After a meeting measured by Read AI, this integration will automatically connect any Contacts, Leads, Accounts, and Opportunities within Salesforce that are related to the external participants who attended the call. Read AI will sync Meeting Report summaries, action items, key questions, and other meeting data directly to those records, providing a comprehensive view of meeting content and progress without leaving Salesforce. This eliminates the need to spend hours updating opportunities. With Read AI, Opportunities are more up-to-date and comprehensive than anything manually written. The integration operates in the background, automatically. For those who prefer not to automatically sync Meeting Reports into Salesforce, Automatic Syncing can be turned off in Integration Settings, allowing individual push of Meeting Reports to Salesforce. To ensure historical Meeting Reports are synced to Salesforce, users can backfill Meeting Report data with one click using the ‘Sync past meetings’ button in Salesforce Integration Settings. For individual sellers, this integration removes the need to block out time to update contacts and opportunities, as Read AI automatically makes those updates. Sales Managers will no longer need to chase down sellers to update their opportunities in Salesforce, allowing more focus on sales strategy with the most complete and timely insights from SFDC. This integration promises a significant boost in productivity for users of both Read AI and Salesforce. Users no longer need to take notes during important sales calls and can easily find meeting details within Salesforce. Read AI empowers sellers to close deals while handling the administrative tasks to ensure opportunities are accurate and updated. 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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August 6, 2024in Salesforce
July Changes to Preference Center
05Aug

July Changes to Preference Center

Privacy Center Update What’s the July Changes to Preference Center? Starting in July 2024, the Privacy Center app within the core platform now supports retention features. July Changes to Preference Center introduces a new Hyperforce-based retention store, allows for retention testing in sandboxes, and offers the option to mask data during retention. The new Hyperforce-based retention store can be provisioned using the core Privacy Center app, eliminating the need for Heroku or the Privacy Center managed package. The rollout of this new retention capability will be phased across regions, initially launching in Germany, Australia, and America East. You can spin up a retention store once it’s available in your region. For more details, refer to the Privacy Center’s Hyperforce-Based Retention Store FAQ. What action do I need to take? What if I don’t take any action? You can continue using the legacy Privacy Center app (managed package version) for data retention, but it will no longer be enhanced and will remain in maintenance mode. Heroku can still be used for managing data retention policies until the end of your contract. Where can I learn more about this upcoming change? Review the Privacy Center’s Hyperforce-Based Retention Store FAQ 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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August 5, 2024in Hyperforce
ChatGPT Word Choices
05Aug

ChatGPT Word Choices

Why Does ChatGPT Use the Word “Delve” So Much? Mystery Solved. The mystery behind ChatGPT’s frequent use of the word “delve” (one of the 10 most common words it uses) has finally been unraveled, and the answer is quite unexpected. Why ChatGPT Word Choices are repetitive. While “delve” and other words like “tapestry” aren’t common in everyday conversations, ChatGPT seems to favor them. You may have noticed this tendency in its outputs. The sudden rise in the use of “delve” in medical papers from March 2024, coincides with the first full year of ChatGPT’s widespread use. “Delve,” along with phrases like “as an AI language model…,” has become a hallmark of ChatGPT’s language, almost a giveaway that a text is AI-generated. But why does ChatGPT overuse “delve”? If it’s trained on human data, how did it develop this preference? Is it emergent behavior? And why “delve” specifically? A Guardian article, “How Cheap, Outsourced Labour in Africa is Shaping AI English,” provides a clue. The key lies in how ChatGPT was built. Why “Delve” So Much? The overuse of “delve” suggests ChatGPT’s language might have been influenced after its initial training on internet data. After training on a massive corpus of data, an additional supervised learning step is used to align the AI’s behavior. Human annotators evaluate the AI’s outputs, and their feedback fine-tunes the model. Here’s a summary of the process: This iterative process involves human feedback to improve the AI’s responses, ensuring it stays aligned and useful. However, this feedback is often provided by a workforce in the global south, where English-speaking annotators are more affordable. In Nigeria, “delve” is more commonly used in business English than in the US or UK. Annotators from these regions provided examples using their familiar language, influencing the AI to adopt a slightly African English style. This is an example of poor sampling, where the evaluators’ language differs from that of the target users, introducing a bias in the writing style. This bias likely stems from the RLHF step rather than the initial training. ChatGPT’s writing style, with or without “delve,” is already somewhat robotic and easy to detect. Understanding these potential pitfalls helps us avoid similar issues in future AI development. Making ChatGPT More Human-Like To make ChatGPT sound more human and avoid overused words like “delve,” consider these Prompt Engineering approaches: These methods can be time-consuming. Ideally, a quick, reliable tool, like a Chrome extension, would streamline this process. If you’ve found a solution or a reliable tool for this issue, share it below in the comments. This is a widespread challenge that many users face. 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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August 5, 2024in Salesforce
July Changes to Marketing Cloud
04Aug

July Changes to Marketing Cloud Growth

You now have access to the new Marketing app, which includes the latest version of Marketing Cloud Growth. This new app replaces the previous Marketing app, now named Marketing (Original). July Changes to Marketing Cloud Growth. What do I need to do – July Changes to Marketing Cloud? To access the new Marketing app, open the App Launcher and select Marketing. For all accounts provisioned prior to Summer ’24, the new Marketing app will be created and it will maintain most of the settings from the Marketing (Original) app. It includes access to all your campaigns and reports. However, you must reconfigure the user access and recreate the customizations that you want to keep. After finishing the setup of the new Marketing app, remove user access to the Marketing (Original) app to avoid using outdated tools. The new Marketing app retains most settings from the Marketing (Original) app, including access to all your campaigns and reports. However, you will need to reconfigure user access and recreate any customizations you want to keep. Learn more in Help. After setting up the new Marketing app, remove user access to the Marketing (Original) app to avoid using outdated tools. Why is this change happening? Beginning Summer ’24 release, Marketing Cloud Growth customers will have access to a new Marketing app. This app replaces the previous Marketing app for Marketing Cloud Growth, which will be renamed Marketing (Original). Newly provisioned accounts will have the Marketing app only.We’ve improved the back end to provide a more streamlined user experience. What if I don’t take action? We will eventually stop supporting the Marketing (Original) app, which may impact your business. Further details will be announced later. How can I get more information? If you have questions regarding the changes to the Marketing app, contact Salesforce Customer Support. 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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August 4, 2024in Salesforce Marketing Cloud, Salesforce Optimization
Ask ChatGPT Vision Action
04Aug

Ask ChatGPT Vision Action

Enhance Your Workflow with the Ask ChatGPT Vision Action Extend the use of artificial intelligence in your daily operations by leveraging the Ask ChatGPT Vision action. This feature allows ChatGPT to analyze images attached to your Salesforce records and apply its insights directly to your workflows. The action is compatible with ChatGPT models that accept image input. How to Use the Ask ChatGPT Vision Action: Create a Macro for Repeated Use: To streamline usage, create a Macro with preconfigured prompts and result fields. Assign the macro to users or profiles to ensure consistent use of the Ask ChatGPT Vision action. Examples: Object Prompt Result Field Case Determine if the image content matches this description: “{!Description}”. Answer “Yes” or “No”. Custom picklist field ‘Attachment matches description’ with values Yes and No Use Cases: For example, use the Ask ChatGPT Vision action to verify if attachments in Cases align with the case’s subject and description. If an attachment matches, automatically route the case to a support agent; otherwise, flag it for review. Expand Your Options: For more flexibility, you can create custom classes and actions to integrate additional data sources or automate further tasks based on ChatGPT’s responses. Explore options like sending emails, creating tasks, or updating records with the information retrieved. For more details on using ChatGPT and managing data privacy, please refer to OpenAI’s website. 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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August 4, 2024in Salesforce
Education Cloud Program Objects
03Aug

Education Cloud Program Objects

Use program objects to track how your learning offerings are structured and administered, and what they require for enrollment and completion. Education Cloud Program Objects let you customize all your programs for ease of use. Programs can be degree or credential programs, academic support programs, recreational programs, continuing education, and more. We use the same architectural building blocks to model each of them in Education Cloud. A Sample Degree Program Offering See an example of how Education Cloud objects represent a program offering. The Biological Sciences Department at Astro University offers an undergraduate Biology degree. This degree program is represented with these objects. To earn the B.S. Biology degree, students complete a sequence of study defined in the university’s course catalog. These high-level requirements for the degree are organized using the learning program plan object. For the student cohort enrolling in the 2023–2024 academic year, a learning program plan record named Biology Catalog Year 2023–2024 represents the set of requirements in effect at that time. When Astro University finalizes its catalog for the next academic year, requirements likely changed slightly and are captured in another Program Plan record named Biology Catalog Year 2024–2025. The learning program plan object represents a general set of requirements. The learning program plan requirement object represents the specific requirements, such as required courses, thesis work, or an internship. To help organize your programs, we recommend that you create accounts for each department or college in your institution. Then, when you create records, assign them to the appropriate account. Manage your program offerings with the Academic Operations app. 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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August 3, 2024in Salesforce, Salesforce Education Cloud
State of AI
03Aug

State of AI

With the Dreamforce conference just a few weeks away, AI is set to be a central theme once again. This week, Salesforce offered a preview of what to expect in September with the release of its “Trends in AI for CRM” report. This report consolidates findings from several Salesforce research studies conducted from February last year to April this year. The report’s executive summary highlights four key insights: The Fear of Missing Out (FOMO) An intriguing statistic from Salesforce’s “State of Data and Analytics” report reveals that 77% of business leaders feel a fear of missing out on generative AI. This concern is particularly pronounced among marketers (88%), followed by sales executives (78%) and customer service professionals (73%). Given the continued hype around generative AI, these numbers are likely still relevant or even higher as of July 2024. As Salesforce AI CEO Clara Shih puts it: “The majority of business executives fear they’re missing out on AI’s benefits, and it’s a well-founded concern. Today’s technology world is reminiscent of 1998 for the Internet—full of opportunities but also hype.” Shih adds: “How do we separate the signal from the noise and identify high-impact enterprise use cases?” The Quest for ROI and Value The surge of hype around generative AI over the past 18 months has led to high expectations. While Salesforce has been more responsible in managing user expectations, many executives view generative AI as a cure-all. However, this perspective can be problematic, as “silver bullets” often miss their mark. Recent tech sector developments reflect a shift toward a longer-term view of AI’s impact. Meta’s share price fell when Mark Zuckerberg emphasized AI as a multi-year project, and Alphabet’s Sundar Pichai faced tough questions from Wall Street about the need for continued investment. State of AI Shih notes a growing impatience with the time required to realize AI’s value: “It’s been over 18 months since ChatGPT sparked excitement about AI in business. Many companies are still grappling with building or buying solutions that are not overly siloed and can be customized. The challenge is finding a balance between quick implementation and configurability.” She adds: “The initial belief was that companies could just integrate ChatGPT and see instant transformation. However, there are security risks and practical challenges. For LLMs to be effective, they need contextual data about users and customers.” Conclusion: A Return to the Future Shih likens the current AI landscape to the late 90s Internet boom, noting: “It’s similar to the late 90s when people questioned if the Internet was overhyped. While some investments will not pan out, the transformative potential of successful use cases is enormous. Just as with the Internet, discovering the truly valuable applications of AI may require experimentation and time. We are very much in the 1998 moment for AI now.” 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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August 3, 2024in Generative AI
AI for Consumers and Retailers
02Aug

AI for Consumers and Retailers

Before generative AI became mainstream, tech-savvy retailers had long been leveraging transformative technologies to automate tasks and understand consumer behavior. Insights from consumer and future trends, along with predictive analytics, have long guided retailers in improving customer experiences and enhancing operational efficiency. AI for Consumers and Retailers improved customer experiences. While AI is currently used for personalized recommendations and online customer support, many consumers still harbor distrust towards AI. Salesforce is addressing this concern by promoting trustworthy AI with human oversight and implementing powerful controls that focus on mitigating high-risk AI outcomes. This approach is crucial as many knowledge workers fear losing control over AI. Although people trust AI to handle significant portions of their work, they believe that increased human oversight would bolster their confidence in AI. Building this trust is a challenge retailers must overcome to fully harness AI’s potential as a reliable assistant. So, where does the retail industry stand with AI, and how can retailers build consumer trust while developing AI responsibly? AI for Consumers and Retailers Recent research from Salesforce and the Retail AI Council highlights how AI is reshaping consumer behavior and retailer interactions. AI is now integral to providing personalized deals, suggesting tailored products, and enhancing customer service through chatbots. Retailers are increasingly embedding generative AI into their business operations. A significant majority (93%) of retailers report using generative AI for personalization, enabling customers to find products and make purchases faster through natural language interactions on digital storefronts and messaging apps. For instance, a customer might tell a retailer’s AI assistant about their camping needs, and based on location, preferences, and past purchases, the AI can recommend a suitable tent and provide a direct link for checkout and store collection. As of early 2024, 92% of retailers’ investments were directed towards AI technology. While AI is not new to retail, with 59% of merchants already using it for product recommendations and 55% utilizing digital assistants for online purchases, its applications continue to expand. From demand forecasting to customer sentiment analysis, AI enhances consumer experiences by predicting preferences and optimizing inventory levels, thereby reducing markdowns and improving efficiency. Barriers and Ethical Considerations Despite its promise, integrating generative AI in retail faces significant challenges, particularly regarding bias in AI outputs. The need for clear ethical guidelines in AI use within retail is pressing, underscoring the gap between adoption rates and ethical stewardship. Strategies that emphasize transparency and accountability are vital for fostering responsible AI innovation. Half of the surveyed retailers indicated they could fully comply with stringent data security standards and privacy regulations, demonstrating the industry’s commitment to protecting consumer data amidst evolving regulatory landscapes. Retailers are increasingly aware of the risks associated with AI integration. Concerns about bias top the list, with half of the respondents worried about prejudiced AI outcomes. Additionally, issues like hallucinations (38%) and toxicity (35%) linked to generative AI implementation highlight the need for robust mitigation strategies. A majority (62%) of retailers have established guidelines to address transparency, data security, and privacy concerns related to the ethical deployment of generative AI. These guidelines ensure responsible AI use, emphasizing trustworthy and unbiased outputs that adhere to ethical standards in the retail sector. These insights reveal a dual imperative for retailers: leveraging AI technologies to enhance operational efficiency and customer experiences while maintaining stringent ethical standards and mitigating risks. Consumer Perceptions and the Future of AI in Retail As AI continues to redefine retail, balancing ethical considerations with technological advancements is essential. To combat consumer skepticism, companies should focus on transparent communication about AI usage and emphasize that humans, not technology, are ultimately in control. Whether aiming for top-line growth or bottom-line efficiency, AI is a crucial addition to a retailer’s technology stack. However, to fully embrace AI, retailers must take consumers on the journey and earn their trust. 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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August 2, 2024in Generative AI
Rold of Small Language Models
02Aug

Role of Small Language Models

The Role of Small Language Models (SLMs) in AI While much attention is often given to the capabilities of Large Language Models (LLMs), Small Language Models (SLMs) play a vital role in the AI landscape. Role of Small Language Models. Large vs. Small Language Models LLMs, like GPT-4, excel at managing complex tasks and providing sophisticated responses. However, their substantial computational and energy requirements can make them impractical for smaller organizations and devices with limited processing power. In contrast, SLMs offer a more feasible solution. Designed to be lightweight and resource-efficient, SLMs are ideal for applications operating in constrained computational environments. Their reduced resource demands make them easier and quicker to deploy, while also simplifying maintenance. What are Small Language Models? Small Language Models (SLMs) are neural networks engineered to generate natural language text. The term “small” refers not only to the model’s physical size but also to its parameter count, neural architecture, and the volume of data used during training. Parameters are numeric values that guide a model’s interpretation of inputs and output generation. Models with fewer parameters are inherently simpler, requiring less training data and computational power. Generally, models with fewer than 100 million parameters are classified as small, though some experts consider models with as few as 1 million to 10 million parameters to be small in comparison to today’s large models, which can have hundreds of billions of parameters. How Small Language Models Work SLMs achieve efficiency and effectiveness with a reduced parameter count, typically ranging from tens to hundreds of millions, as opposed to the billions seen in larger models. This design choice enhances computational efficiency and task-specific performance while maintaining strong language comprehension and generation capabilities. Techniques such as model compression, knowledge distillation, and transfer learning are critical for optimizing SLMs. These methods enable SLMs to encapsulate the broad understanding capabilities of larger models into a more concentrated, domain-specific toolset, facilitating precise and effective applications while preserving high performance. Advantages of Small Language Models Applications of Small Language Models Role of Small Language Models is lengthy. SLMs have seen increased adoption due to their ability to produce contextually coherent responses across various applications: Small Language Models vs. Large Language Models Feature LLMs SLMs Training Dataset Broad, diverse internet data Focused, domain-specific data Parameter Count Billions Tens to hundreds of millions Computational Demand High Low Cost Expensive Cost-effective Customization Limited, general-purpose High, tailored to specific needs Latency Higher Lower Security Risk of data exposure through APIs Lower risk, often not open source Maintenance Complex Easier Deployment Requires substantial infrastructure Suitable for limited hardware environments Application Broad, including complex tasks Specific, domain-focused tasks Accuracy in Specific Domains Potentially less accurate due to general training High accuracy with domain-specific training Real-time Application Less ideal due to latency Ideal due to low latency Bias and Errors Higher risk of biases and factual errors Reduced risk due to focused training Development Cycles Slower Faster Conclusion The role of Small Language Models (SLMs) is increasingly significant as they offer a practical and efficient alternative to larger models. By focusing on specific needs and operating within constrained environments, SLMs provide targeted precision, cost savings, improved security, and quick responsiveness. As industries continue to integrate AI solutions, the tailored capabilities of SLMs are set to drive innovation and efficiency across various domains. 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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August 2, 2024in Salesforce
Healthcare IT Lessons from CrowdStrike
02Aug

Healthcare IT Lessons from CrowdStrike

Post-Outage Recovery and Lessons from the CrowdStrike Incident Following the CrowdStrike outage on July 19, 2024, companies globally have been working to restore business continuity and enhance their resilience for future incidents. The outage, caused by a faulty content update, led to crashes on approximately 8.5 million Windows devices, affecting hospitals, airlines, and other businesses. Although less than 1% of all Windows machines were impacted, the incident caused significant disruptions, including appointment cancellations at hospitals. For instance, Mass General Brigham canceled all non-urgent visits on the day the outage began. Other healthcare organizations, such as Memorial Sloan Kettering Cancer Center, Cleveland Clinic, and Mount Sinai, also faced operational challenges. The cause of the outage was a defective content configuration update to CrowdStrike’s Falcon threat detection platform, not a cyberattack. A bug in the content validator allowed the faulty update to bypass validation, as noted in CrowdStrike’s preliminary post-incident review. David Finn, Executive Vice President of Governance, Risk, and Compliance at First Health Advisory, shared with TechTarget Editorial, “The recovery is well underway, and most healthcare organizations are back up and running. While the scope was smaller compared to other recent incidents in healthcare, the response was effective. There are valuable lessons to be learned.” Preparing for Future Incidents Finn, with 40 years of experience in health IT security, emphasized that incidents are inevitable. “The challenge is to plan, prepare, and be able to recover and stay resilient,” he stated. Whether facing a major cyberattack like the February 2024 Change Healthcare incident or an IT outage without malicious intent, healthcare organizations must be ready for various cyber incidents affecting critical systems. He highlighted the importance of thorough due diligence and incident response planning. Addressing potential operational challenges in advance and planning for cybersecurity events or IT failures will prove beneficial when an incident occurs. “We need to rethink how we deploy software,” Finn added. “Human errors will always happen, and it’s our job to protect against those mistakes.” Building Cyber-Resilience Cyber-resilience is crucial for quickly recovering and resuming operations. Organizations should anticipate incidents and focus on building resilience. Finn noted, “While I still trust CrowdStrike, trust does not guarantee perfection. Resilience and redundancy are vital.” Healthcare organizations responded swiftly to the CrowdStrike incident, with Mass General Brigham activating its incident command to manage the situation. The organization ensured that clinics and emergency departments remained open for urgent health concerns and resumed scheduled appointments and procedures by July 22. Evaluating Risk and Updating Protocols Erik Weinick, co-head of the privacy and cybersecurity practice at Otterbourg, urged organizations to use the CrowdStrike incident as an opportunity to reevaluate their risk management protocols. “Even if the incident was accidental, organizations should conduct information audits, penetration testing, update system mappings, and reinforce security practices like multifactor authentication and strong password policies.” Addressing Third-Party Risk The outage underscored the importance of managing third-party risks. The interconnectedness of healthcare systems amplifies these risks, as evidenced by some of the largest healthcare data breaches in recent years originating from third-party vendors. Finn suggested that while organizations may conduct risk analyses on vendors like CrowdStrike, they should also inquire about the tools used in software development. “We need standards and certifications for software used in critical infrastructure sectors,” he said. In response to the incident, CrowdStrike committed to enhancing its software resilience by adding more validation checks and conducting independent third-party security code reviews. Weinick advised reviewing vendor agreements, updating business disruption insurance coverage, and conducting tabletop exercises to rehearse business continuity and recovery procedures for all potential disruptions. Overall, the CrowdStrike outage highlighted critical IT and security considerations, emphasizing the need for resilience, effective third-party risk management, and robust incident response and recovery plans. 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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August 2, 2024in Salesforce

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