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Salesforce Healthcare and AI
11Sep

Salesforce Healthcare and AI

The Healthcare Industry’s Digital Transformation: An Opportunity Unveiled – Salesforce Healthcare and AI Historically, the healthcare sector has lagged behind in technology adoption, particularly software. It consistently invests less in IT and software compared to other industries, relying heavily on manual processes and outdated tools like faxes and phone calls. Unlike other sectors where platforms like Salesforce, Slack, JIRA, and Notion dominate, healthcare has yet to see similar technological integration. Salesforce Healthcare and AI Future While this low adoption of software has previously been seen as a drawback, it now presents a significant opportunity. Unlike industries burdened by extensive investments in legacy systems, healthcare is not encumbered by sunk costs. This freedom allows it to embrace cutting-edge AI innovations without the hesitation of overhauling existing, expensive software infrastructures. Addressing the Staffing Crisis The healthcare industry is grappling with a severe staffing crisis, with a shortfall of over 100,000 doctors and nurses projected over the next five years. The increasing complexity of medical care, driven by advancements in diagnostics, continuous monitoring, and new treatments, contributes to an overwhelming amount of information for clinicians. To manage this, healthcare requires new tools capable of processing complex data in real-time to support critical decisions for an aging population with more complex health needs. The most valuable asset in healthcare is clinical judgment, which is currently exclusive to human practitioners. A major challenge is to extend this clinical judgment beyond the existing workforce and physical locations, making it accessible to all who need it. Additionally, ensuring that every clinician performs at the highest level is crucial. The Role of Administrative and Clinical AI Administrative AI is essential for reducing the overhead of healthcare delivery, allowing for better resource management and efficiency. Clinical AI products, though challenging to develop due to their high-stakes nature, are uniquely positioned to address these needs. They must integrate seamlessly into existing environments, adding a layer of sophistication to healthcare processes. Regulatory Advantages for Clinical AI One of healthcare’s advantages in adopting AI is its well-established regulatory framework. The FDA has approved numerous clinical AI products and is developing processes to keep pace with advancements in machine learning and generative AI. This rigorous approval process ensures that only the most reliable and clinically sound products make it to market, creating a higher barrier to entry but also a stronger competitive advantage for those that succeed. The Scale of Opportunity The healthcare industry is a massive $4 trillion+ market, predominantly driven by human labor rather than technology. Historically, enterprise software companies have struggled to penetrate this sector, as IT budgets represent just 3.5% of revenue—less than half of that in financial services. However, with AI tools advancing rapidly, they are increasingly seen as “AI staff” rather than mere software. This shift opens up opportunities not just in software but in transforming service delivery, potentially disrupting a market valued in trillions rather than billions. The scale of this opportunity far exceeds past software ventures, as reflected in the significant capital and valuations flowing into AI-driven healthcare companies. Whether you’re launching a new clinic, developing infrastructure for the healthcare system, or creating innovative payment or insurance models, now is an unprecedented time to enter the healthcare space. The transformative power of AI is poised to redefine how healthcare companies are built, scaled, and brought to market. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 11, 2024in Generative AI, Life Sciences Cloud, Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud, Salesforce Managed Services, Salesforce Optimization
Salesforce and Tenyx
10Sep

Salesforce and Tenyx

Salesforce has announced its acquisition of AI voice agent firm Tenyx, with the deal expected to close in the third quarter. While the financial terms have not been disclosed, Tenyx’s co-founders, CEO Itamar Arel and CTO Adam Earle, along with their team, will join Salesforce as part of the acquisition. This move comes after Salesforce, under pressure from activist investors, previously shifted away from acquisitions and increased its share buybacks following the dissolution of its mergers and acquisitions committee. However, the company is now pursuing strategic acquisitions to boost revenue growth. Conversational AI forthe Enterprise Tenyx Voice is an Interactive Virtual Agent (IVA) built from the ground up leveraging today’s modern AI stack. Built by a team with a proven track record in voice AI, and leveraging a unique core AI and voice platform, Tenyx promises to redefine customer interactions for the enterprise. Tenyx Voice is an Interactive Virtual Agent (IVA) built from the ground up leveraging today’s modern AI stack. Built by a team with a proven track record in voice AI, and leveraging a unique core AI and voice platform, Tenyx promises to redefine customer interactions for the enterprise. Industries and Use Cases If 2023 was the year of large language models (LLMs), 2024 is shaping up to be the year of voice agents. When ChatGPT made waves globally, startups, tech firms, and entrepreneurs rushed to discover business use cases for the new technology. The ideal applications targeted tasks that are costly, time-consuming, and hard to scale. Voice agents and automated customer service systems quickly emerged as one of the most promising solutions. However, many companies deploying these systems aren’t fully considering their impact on customers. That’s why Tenyx is launching its inaugural Voice AI Consumer Report. We surveyed hundreds of Americans across different age groups, races, geographies, and genders to better understand their preferences and experiences with AI-powered voice agents. Here are the key findings: What this means: Frustrating Calls Hurt Your Brand Imagine calling customer service for a quick solution, only to be met by an automated voice agent that can’t understand your request or handle complex issues. It’s a common and frustrating experience. Our data shows that nearly 7 in 10 people express frustration or annoyance with today’s automated voice agents—sentiments that can severely damage customer loyalty and business outcomes. “Our report highlights a major disconnect between consumer expectations and the performance of current automated voice agents,” says Itamar Arel, CEO of Tenyx. “While these systems promise efficiency and cost savings, they often fall short when it comes to addressing consumers’ nuanced needs.” Incomplete AI Systems Drive Customer Churn Subpar AI systems are driving customers away. Two-thirds of respondents said they wouldn’t return to a company after a negative experience with its AI voice agent. In fact, 67% still prefer interacting with human agents over automated ones. Why? Current AI voice agents struggle with complex issues and fail to provide the empathy and problem-solving skills that human agents, or more advanced AI systems, offer. Selective Deployment and Industry-Specific Agents Matter Our data shows that consumers are more accepting of voice agents in certain industries than others. Sectors like healthcare, restaurants, and telecoms saw the highest satisfaction with AI voice agents, while airlines, banking, and hotels ranked the lowest. This highlights the importance of selective deployment and tailoring voice agents for specific industries to better meet customer needs. Looking Ahead: The Promise of Perfect Automation Despite the skepticism, there’s hope. Two-thirds of respondents indicated they’d embrace automated voice agents if these systems could match the performance of human agents. This is exactly what we’re working on at Tenyx—building scalable, reliable AI agents that serve businesses and customers globally. “As leaders in voice AI technology, Tenyx is dedicated to closing the gap between consumer expectations and technological capabilities,” Arel says. “Our mission is to equip businesses with AI solutions that not only streamline operations but also boost customer satisfaction.” 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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September 10, 2024in Salesforce
Army of AI Bots
09Sep

Army of AI Bots

Salesforce Inc. has announced a significant upgrade with the launch of Industries AI, a new automation platform designed to handle a wide range of time-consuming tasks, enhancing productivity across various sectors. We are NOT advocating that the next war will be fought with AI Bots. We aren’t even suggesting there is anything negative about these bots. However, if the next war were to be information and data based, who knows. Industries AI will be integrated into all 15 of Salesforce’s cloud platforms, including Sales Cloud, Data Cloud, Service Cloud, Commerce Cloud, and Marketing Cloud. This expansive solution is capable of managing over 100 common tasks, from matching patients with clinical trials and providing maintenance alerts for vehicles and machinery, to streamlining recruitment processes and enhancing government services. The launch of Industries AI responds to findings from Salesforce’s Trends in AI for CRM Report, which indicated that over 75% of business leaders are concerned about missing out on AI advancements if they do not adopt the technology soon. With a 700% increase in urgency to implement AI over the past six months, many organizations struggle with the resources and expertise needed to develop and train AI models. Salesforce aims to address this by offering a ready-made framework for creating AI agents tailored to industry-specific needs, utilizing each customer’s proprietary data within the Salesforce platform. Industries AI will provide a foundation for quickly deploying autonomous agents, with setup times estimated at just a few minutes. To assist customers in leveraging AI automation, Salesforce has created use case libraries for each of its cloud platforms, featuring over 100 capabilities at launch. These capabilities span multiple industries: Salesforce will begin rolling out Industries AI capabilities in October 2024, with some features available by February 2025. The company plans to regularly update Industries AI with new capabilities as part of its annual Salesforce releases. Jeff Amann, executive vice president and general manager of Salesforce Industries, emphasized that this innovation aims to make powerful AI accessible to all enterprises, regardless of size or budget. “Organizations can now easily start with AI solutions tailored to their specific challenges, enhancing efficiency and productivity across various functions,” he said. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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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September 9, 2024in Generative AI
AI-Powered Field Service
09Sep

AI-Powered Field Service

Salesforce has introduced new AI-powered field service capabilities designed to streamline operations for dispatchers, technicians, and field service leaders. Leveraging the Salesforce platform and Data Cloud, these innovations aim to expedite time-consuming processes and enhance customer satisfaction by making field service operations more proactive and efficient. Why it matters: Field service teams currently spend only 32% of their time interacting with customers, with the remaining 68% consumed by administrative tasks like manually entering case notes. With 78% of field service workers in AI-enabled organizations reporting that AI helps save time, Salesforce’s new tools address these inefficiencies head-on. Key AI-driven innovations for Field Service: Availability: Paul Whitelam, GM & SVP of Salesforce Field Service, notes, “The future of field service lies in the seamless integration of AI, data, and human expertise. Our new capabilities set new standards for efficiency and service delivery.” Rudi Khoury, Chief Digital Officer at Fisher & Paykel, adds, “With Salesforce Field Service, we’re not just embracing AI and data-driven insights — we’re advancing into the future of field service, achieving unprecedented efficiency and exceptional service.” 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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September 9, 2024in Einstein Insights, Salesforce Development Services, Salesforce Manufacturing Automotive Energy, Salesforce Service Cloud
Predictive Analytics
09Sep

Predictive Analytics

Industry forecasts predict an annual growth rate of 6% to 7%, fueled by innovations in cloud computing, artificial intelligence (AI), and data engineering. In 2023, the global data analytics market was valued at approximately $41 billion and is expected to surge to $118.5 billion by 2029, with a compound annual growth rate (CAGR) of 27.1%. This significant expansion reflects the growing demand for advanced analytics tools that provide actionable insights. AI has notably enhanced the accuracy of predictive models, enabling marketers to anticipate customer behaviors and preferences with impressive precision. “We’re on the verge of a new era in predictive analytics, with tools like Salesforce Einstein Data Analytics revolutionizing how we harness data-driven insights to transform marketing strategies,” says Koushik Kumar Ganeeb, a Principal Member of Technical Staff at Salesforce Data Cloud and a distinguished Data and AI Architect. Ganeeb’s leadership spans initiatives like AI-powered Salesforce Einstein Data Analytics, Marketing Cloud Connector for Data Cloud, and Intelligence Reporting (Datorama). His expertise includes architecting vast data extraction pipelines that process trillions of transactions daily. These pipelines play a crucial role in the growth strategies of Fortune 500 companies, helping them scale their data operations efficiently by leveraging AI. Ganeeb’s visionary work has propelled Salesforce Einstein Data Analytics into the forefront of business intelligence. Under his guidance, the platform’s advanced capabilities—such as predictive modeling, real-time data analysis, and natural language processing—are now pivotal in transforming how businesses forecast trends, personalize marketing efforts, and make data-driven decisions with unprecedented precision. AI and Machine Learning: The Next Frontier Beginning in 2018, Salesforce Marketing Cloud, a leading engagement platform used by top enterprises, faced challenges in extracting actionable insights and enhancing AI capabilities from rapidly growing data across diverse systems. Ganeeb was tasked with overcoming these hurdles, leading to the development of the Salesforce Einstein Provisioning Process. This process involved the creation of extensive data import jobs and the establishment of standardized patterns based on consumer adoption learning. These automated jobs handle trillions of transactions daily, delivering critical engagement and profile data in real-time to meet the scalability needs of large enterprises. The data flows seamlessly into AI models that generate predictions on a massive scale, such as Engagement Scores and insights into messaging and language usage across the platform. “Integrating AI and machine learning into data analytics through Salesforce Einstein is not just a technological enhancement—it’s a revolutionary shift in how we approach data,” explains Ganeeb. “With our advanced predictive models and real-time data processing, we can analyze vast amounts of data instantly, delivering insights that were previously unimaginable.” This innovative approach empowers organizations to make more informed decisions, driving unprecedented growth and operational efficiency. Real-World Success Stories Under Ganeeb’s technical leadership, Salesforce Einstein Data Analytics has delivered remarkable results across industries by leveraging AI and machine learning to provide actionable insights and enhance business performance. In the past year, leading companies like T-Mobile, Fitbit, and Dell Technologies have reported significant improvements after integrating Einstein. Ganeeb’s proficiency in designing and scaling data engineering solutions has been critical in helping these enterprises optimize performance. “Scalability with Salesforce Einstein Data Analytics goes beyond managing data volumes—it ensures that every data point is converted into actionable insights,” says Ganeeb. His work processing petabytes of data daily underscores his commitment to precision and efficiency in data engineering. Navigating Data Ethics and Quality Despite the rapid growth of predictive analytics, Ganeeb emphasizes the importance of data ethics and quality. “The accuracy of predictive models depends on the integrity of the data,” he notes. Salesforce Einstein Data Analytics addresses this by curating datasets to ensure they are representative and free from bias, maintaining trust while delivering reliable insights. By implementing rigorous data quality checks and ethical considerations, Ganeeb ensures that Einstein Analytics not only delivers actionable insights but also fosters transparency and trust. This balanced approach is key to the responsible use of predictive analytics across various industries. Future Trends in Predictive Analytics The future of predictive analytics looks bright, with AI and machine learning poised to further refine the accuracy and utility of predictive models. “Success lies in embracing technological advancements while maintaining a human touch,” Ganeeb notes. “By combining AI-driven insights with human intuition, businesses can navigate market complexities and uncover new opportunities.” Ganeeb’s contributions to Salesforce Einstein Data Analytics exemplify this balanced approach, integrating cutting-edge technology with human insight to empower businesses to make strategic decisions. His work positions organizations to thrive in a data-driven world, helping them stay agile and competitive in an evolving market. Balancing Benefits and Challenges – Predictive Analytics While predictive analytics offers vast potential, Ganeeb recognizes the challenges. Ensuring data quality, addressing ethical concerns, and maintaining transparency are crucial for its responsible use. “Although challenges remain, the future of AI-based predictive analytics is promising,” Ganeeb asserts. His work with Salesforce Einstein Data Analytics continues to push the boundaries of marketing analytics, enabling businesses to harness the power of AI for transformative growth. 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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September 9, 2024in Salesforce Data Cloud, Salesforce Einstein, Salesforce Marketing Cloud
Salesforce AI Agents Explained
09Sep

Salesforce AI Agents Explained

Salesforce’s AI Agents: Revolutionizing Enterprise Sales and Service for the Future In the rapidly evolving landscape of artificial intelligence (AI), Salesforce continues to lead the charge, transforming enterprise operations with cutting-edge AI agents. With the introduction of Agentforce, Salesforce is not just enhancing sales and service departments but reshaping business processes across sectors. This comprehensive exploration highlights how Salesforce’s AI agents are changing the game, offering enterprise-level executives insights into their revolutionary potential. Salesforce AI Agents Explained. AI Agents: Beyond Autonomous Vehicles A fitting analogy to grasp the progression of AI agents is the evolution of autonomous vehicles. Just as self-driving cars advance from basic driver assistance to full autonomy, AI agents evolve from simple automation to more complex decision-making. Salesforce’s Chief Product Officer, David Schmaier, draws this comparison: “In the autonomous driving world, we have levels of autonomy, from level zero to level five. AI agents for enterprises follow a similar path.” At the core of this evolution is what Salesforce defines as the “agentic” phase of AI. Unlike generative AI that follows instructions to create content, agentic AI autonomously determines and takes actions based on broader goals. Schmaier notes, “We’re at the point where AI not only creates content but takes strategic actions. It’s like having an infinite pool of interns handling mundane tasks so human employees can focus on higher-value activities.” Agentforce: Salesforce’s Next-Generation AI Platform Agentforce is the latest addition to Salesforce’s AI arsenal, unveiled during their Q2 ’25 earnings call and now positioned as a significant milestone in AI development. With Agentforce, organizations can build and manage autonomous agents for tasks across various business functions—not just customer service. This versatility is highlighted by Marc Benioff, Salesforce’s CEO, who described the energy around Agentforce during a recent briefing as “palpable.” Agentforce builds on Salesforce’s data management, security, and customization expertise, uniting these capabilities into an AI framework. Schmaier explains, “It’s about creating trusted, enterprise-ready agents, not just deploying a large language model. We’ve developed over 100 out-of-the-box use cases, from sales account summaries to service reply recommendations, all customizable and easy to deploy.” Agentforce “In Every App” A key announcement is the integration of Agentforce in every app across Salesforce’s product suite, including Sales, Service, Marketing, and Commerce Agents. The Atlas reasoning engine, Agent Builder, and a partner network were also introduced to further enhance its capabilities. The Atlas Reasoning Engine acts as the “brain” behind Agentforce, autonomously generating plans and refining them based on actions it needs to perform, such as running business processes or engaging customers through preferred channels. What Makes an AI Agent? Salesforce AI Agents Explained Building an AI agent with Agentforce requires five key elements: These components leverage existing Salesforce infrastructure, making it easier for businesses to deploy agents through Agent Builder, which is part of the new Agentforce Studio. Agents vs. Chatbots Unlike traditional chatbots, which provide pre-programmed responses, Salesforce’s AI agents use large language models (LLMs) and generative AI to interpret and autonomously execute customer requests based on CRM data. This distinction allows AI agents to perform tasks that go beyond simple queries, driving efficiency in customer service, sales, and other business areas. Practical Applications: Sales, Service, and Marketing Salesforce’s AI agents offer tangible business benefits. For instance, Sales Agent, available as both a Sales Development Representative (SDR) and Sales Coach, automates lead nurturing and inquiry management. It utilizes CRM data to deliver personalized pitches, handle objections, and even suggest meeting times—freeing sales teams to focus on more strategic tasks. In customer service, AI agents manage routine inquiries, allowing human representatives to address more complex customer needs. In marketing, AI agents generate data-driven insights to personalize campaigns, improving customer engagement and conversion rates. The Security and Trust Foundation Security and trust remain core to Salesforce’s approach to AI. The Einstein Trust Layer ensures that data protection, privacy, and ethical guidelines are maintained throughout AI interactions. Schmaier emphasizes, “Our platform defines what data agents can access and how they use it, adhering to strict data integrity standards.” The Trust Layer also prevents AI from training on customer data without consent, ensuring transparency and security. A Partnership Between Humans and AI-Salesforce AI Agents Explained Salesforce’s vision emphasizes the synergy between human employees and AI agents. As Schmaier points out, “AI agents handle routine tasks and deliver insights, allowing employees to focus on more creative and strategic work.” This human-AI partnership boosts productivity and innovation, ultimately improving business outcomes. The Future of AI in Business As AI technology advances, Salesforce is already working on next-generation capabilities for Agentforce, including predictive analytics and more sophisticated autonomous agents. Schmaier forecasts, “These agents will handle a wider range of tasks and provide deeper insights and recommendations.” With Agentforce launching in October 2024, businesses can expect significant returns on investment, thanks to its cost-efficient model starting at $2 per conversation. In summary, Salesforce’s Agentforce is a game-changing innovation, blending AI and human intelligence to transform sales, service, and marketing. As more details unfold, it’s clear that Agentforce will redefine the future of business operations—driving efficiency, personalization, and strategic success. 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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September 9, 2024in Agentforce Platform, Generative AI, Technology
Slack Expands AI Features
08Sep

Slack Expands AI Features

Slack is introducing several new AI-driven features, including the integration of AI-powered agents from Salesforce and other leading partners across the platform. The Big Picture: As part of its evolution, the Salesforce-owned company aims to position Slack as a hub where humans collaborate seamlessly with an increasing number of bots and AI agents. Key Updates: Ahead of Salesforce’s Dreamforce conference, Slack announced its support for agents from partners such as Adobe, Anthropic, Cohere, Perplexity, Writer, and more, alongside Salesforce’s own Agentforce. Additionally, Slack is enhancing its AI capabilities, expanding its AI-driven transcription features to include informal video chat sessions, known as “huddles.” Why It Matters: This move aligns with Salesforce’s broader strategy of leveraging generative AI to power autonomous agents that can take independent action, moving beyond the traditional role of AI as a co-pilot merely assisting humans. What They’re Saying: “Slack’s vision of becoming an AI-powered work operating system fits perfectly with the growing role of agents in the workplace,” said Slack CEO Denise Dresser in a statement to Axios. While Dresser didn’t disclose how many paying customers have adopted Slack’s AI features, it’s worth noting that these features require a separate monthly fee. Initially, Slack planned to require companies to pay for AI features for all users or none, but the company later shifted this approach following customer feedback. And Slack Expands AI Features with New Agent Integrations Slack is introducing several new AI-driven features, including the integration of AI-powered agents from Salesforce and other leading partners across the platform. The Big Picture: As part of its evolution, the Salesforce-owned company aims to position Slack as a hub where humans collaborate seamlessly with an increasing number of bots and AI agents. Key Updates: Ahead of Salesforce’s Dreamforce conference, Slack announced its support for agents from partners such as Adobe, Anthropic, Cohere, Perplexity, Writer, and more, alongside Salesforce’s own Agentforce. Additionally, Slack is enhancing its AI capabilities, expanding its AI-driven transcription features to include informal video chat sessions, known as “huddles.” Why It Matters: This move aligns with Salesforce’s broader strategy of leveraging generative AI to power autonomous agents that can take independent action, moving beyond the traditional role of AI as a co-pilot merely assisting humans. What They’re Saying: “Slack’s vision of becoming an AI-powered work operating system fits perfectly with the growing role of agents in the workplace,” said Slack CEO Denise Dresser in a statement to Axios. While Dresser didn’t disclose how many paying customers have adopted Slack’s AI features, it’s worth noting that these features require a separate monthly fee. Initially, Slack planned to require companies to pay for AI features for all users or none, but the company later shifted this approach following customer feedback. 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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September 8, 2024in Generative AI
AI in Performance Management
08Sep

AI in Performance Management

AI in Performance Management: Benefits and Use Cases AI is making its way into all aspects of the workplace, and performance management is no exception. While the technology can streamline performance reviews and enhance feedback quality, HR leaders should be mindful of potential drawbacks, such as impersonal or overly generic feedback. Here’s a look at how AI can be used in performance management, along with its advantages and some challenges to consider. 4 Benefits of Using AI in Performance Management AI can offer several advantages for companies in terms of improving employee feedback and overall performance. Here are four key benefits: 1. Faster Employee Feedback Creation AI can help managers draft initial feedback for employees, saving time and effort. By setting parameters like years in the role or specific job metrics, AI-generated feedback can be more accurate. However, managers should review and personalize the feedback to ensure it feels relevant and human. 2. Enhanced Feedback Quality AI tools can analyze performance review drafts, identifying issues like repetitive wording, biased language, or inappropriate tone. By refining the text, AI helps managers deliver more thoughtful and effective feedback. 3. Better Reporting and Dashboards AI can analyze performance data and generate reports or dashboards, providing senior leaders and HR teams with a clear overview of employee performance. This capability is especially useful for large companies with substantial data, helping decision-makers track progress and identify trends. 4. Boosted Employee Performance By simplifying the review process, AI can encourage managers to provide feedback more frequently. Regular, timely feedback keeps employees focused, motivated, and aligned with company goals, enhancing their development and overall experience. 4 Use Cases for AI in Performance Management AI’s role in performance management goes beyond feedback creation. Here are four specific ways AI can streamline the process: 1. Employee Data Analysis AI can aggregate and analyze various employee data sources—such as past performance reviews or internal communications—summarizing key insights for managers. This saves time spent on manual data gathering, though managers should still verify the data and focus on the most relevant information. 2. Generating Discussion Topics AI can generate discussion prompts for managers to use in one-on-one meetings with employees, such as future career goals or project challenges. While this saves time, managers should tailor the AI suggestions to the individual employee to ensure relevance. 3. Career Path Generation AI can suggest potential career paths for employees, pointing out skills or training required for advancement. While helpful, managers should rely on company-specific career progression frameworks when available, as these tend to be more tailored to the organization’s needs. 4. Feedback Reminders AI can automatically remind managers to provide feedback to their direct reports, helping maintain a regular cadence of performance reviews. Additionally, AI can flag anomalies in feedback frequency, ensuring that employees receive consistent input throughout the year. Key Takeaways for HR Leaders While AI can significantly enhance the efficiency and effectiveness of performance management, it’s essential to remember that human oversight is critical. AI can automate processes and improve feedback, but managers should always review AI-generated content for accuracy and appropriateness to maintain a personal connection with their employees. By leveraging AI thoughtfully, companies can improve performance management processes, offer more frequent feedback, and drive better employee 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 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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September 8, 2024in Salesforce
Salesforce to Enhance AI-Powered Tools With Tenyx
07Sep

Salesforce to Enhance AI-Powered Tools With Tenyx

Salesforce to Acquire Tenyx, Enhancing AI-Powered Solutions Salesforce has announced its decision to acquire Tenyx, a California-based startup specializing in AI-driven voice agents. This acquisition aims to bolster Salesforce’s AI capabilities and further its commitment to enhancing customer service through innovative technology. The deal, set to close in the third quarter of 2024, will integrate Tenyx’s advanced voice AI solutions with Salesforce’s existing services. About Tenyx Founded in 2022, Tenyx has quickly established itself in various industries including e-commerce, healthcare, hospitality, and travel. The startup, led by CEO Itamar Arel and CTO Adam Earle, is renowned for developing AI voice agents that create natural and engaging conversational experiences. Salesforce’s Strategic Move This acquisition is part of Salesforce’s broader strategy to reinvigorate its growth and strengthen its AI capabilities. Following a year of focus on share buybacks and a reduction in acquisitions under pressure from activist investors, Salesforce is now pivoting to integrate cutting-edge technology. This move reflects a renewed emphasis on acquiring top-tier AI talent to drive innovation and maintain a competitive edge. Industry Context The acquisition aligns Salesforce with a growing trend in the tech industry, where major players like Microsoft and Amazon are also investing heavily in AI. Microsoft recently acquired talent from AI startup Inflection for $650 million, while Amazon brought in co-founders and employees from Adept. These strategic acquisitions highlight the escalating competition for AI expertise and tools. What This Means for Salesforce With Tenyx’s technology, Salesforce will enhance its AI-powered solutions, particularly within its Agentforce Service Agent platform. This integration aims to deliver more intuitive and seamless customer interactions, setting new standards in customer experience. Conclusion Salesforce’s acquisition of Tenyx is a strategic move to advance its AI-driven solutions and maintain its leadership in customer service technology. By integrating Tenyx’s innovative voice AI, Salesforce is positioned to redefine customer engagement and service standards. The deal is expected to close by the end of the third quarter of Salesforce’s fiscal year 2025, concluding on October 31, 2024, pending customary closing conditions. 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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September 7, 2024in Salesforce, Technology
Adopting Salesforce Security Policies
07Sep

Adopting Salesforce Security Policies

Data breaches reached an all-time high in 2023, affecting more than 234 million individuals, and there’s no sign of the trend slowing down. At the center of this challenge is how organizations allocate resources to safeguard customer data. One of the most critical systems for managing this data is CRM platforms like Salesforce, used by over 150,000 U.S. businesses. However, security blind spots within Salesforce continue to pose significant risks. To address these concerns, the National Institute of Standards and Technology (NIST) offers a strategic framework for Salesforce security teams. In February 2024, NIST released Version 2.0 of its Cybersecurity Framework (CSF), marking the first major update in a decade. Key improvements include the introduction of a new “Govern” function, streamlining of categories to simplify usability, and updates to the “Respond” function to enhance incident management. This framework now applies across all industries, not just critical infrastructure. For Salesforce security leaders, these changes will significantly affect how they manage security, from aligning Salesforce practices with enterprise risk strategies to strengthening oversight of third-party apps. Here’s how these updates will influence Salesforce security going forward. What is the NIST Cybersecurity Framework 2.0? The NIST Cybersecurity Framework, first launched in 2014, was developed after an executive order by President Obama, aiming to provide a standardized set of guidelines to improve cybersecurity across critical infrastructure. The framework’s objectives include: The newly updated NIST CSF 2.0, released in 2024, expands on the original framework, providing organizations with structured, yet flexible, guidance for managing cybersecurity risks. It revolves around three core components: the CSF Core, CSF Profiles, and CSF Tiers. Key Components of NIST Cybersecurity Framework 2.0 These components help organizations understand, assess, and improve their cybersecurity posture, forming the basis for risk-informed strategies that align with organizational needs and the evolving threat landscape. Key Updates in the NIST Cybersecurity Framework 2.0 and Their Impact on Salesforce Security The 2024 updates to NIST CSF offer insights that Salesforce security leaders can use to align their strategies with evolving cybersecurity risks. Implementation Strategies for Salesforce Security Leaders To incorporate CSF 2.0 into Salesforce security operations, leaders should: Conclusion: Embracing NIST CSF 2.0 to Strengthen Salesforce Security The 2024 NIST Cybersecurity Framework updates offer crucial insights for Salesforce security leaders. By adopting these practices, organizations can enhance data protection, strengthen incident response capabilities, and ensure business continuity—critical for those relying on Salesforce for managing sensitive customer data. 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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September 7, 2024in Data, Enterprise, Salesforce, Salesforce Shield, Technology
Citizen Development
06Sep

Citizen Development

As we progress through the era of digital transformation, citizen development has emerged as a key trend in the business landscape. This approach empowers end-users to create their applications, streamlining workflows and reshaping corporate operations. However, like any innovation, citizen development presents both advantages and challenges. In this article, we will explore the benefits, pros and cons of citizen development, and strategies to effectively leverage it within your organization. 1. The Rise of Citizen Development The popularity of citizen development is on the rise, as reflected by Statista, which reports a remarkable 24.6% growth in this sector since 2020. The increasing demand for software solutions in the corporate environment has made the traditional model of IT departments solely managing application development unsustainable. By enabling non-technical personnel to develop their applications, businesses can relieve pressure on IT teams, speed up solution delivery, and cultivate a more agile business model. Furthermore, investing in citizen development platforms fosters an inclusive and innovative workplace, allowing diverse perspectives to generate unique applications that meet specific workflow needs. 2. Benefits of Citizen Development for Companies 2.1 Accelerated Pace and Flexibility Citizen development tools facilitate rapid prototyping and quicker application rollouts. Non-technical personnel can design, modify, and launch applications according to immediate needs, enhancing agility and responsiveness. 2.2 Boosted Creativity Empowering your staff to create applications unlocks a wealth of untapped potential. Citizen development nurtures a culture of innovation, leading to tailored solutions that address specific business challenges. 2.3 Tailored App Design Citizen developers, as end-users, possess an in-depth understanding of their workflow requirements. This perspective enables them to develop applications that align closely with user needs, improving adoption and utility. 2.4 Heightened Productivity By reducing the back-and-forth between IT departments and end-users, citizen development streamlines operations, leading to enhanced efficiency. 2.5 Cost-Effectiveness Citizen development significantly cuts costs associated with traditional application development, such as hiring professional developers or outsourcing tasks. Rapid application rollouts also help seize business opportunities quickly, optimizing ROI. 2.6 Reduced Workload for IT Staff Enabling non-technical personnel to handle minor application development tasks lightens the load on IT teams, allowing them to focus on high-priority projects. 2.7 Enhanced Visibility and Accountability Many citizen development platforms include built-in analytics and reporting features, offering insights into application usage and performance. This transparency helps businesses track initiatives, make data-driven decisions, and continuously improve processes. 3. Implementing Citizen Development with Salesforce Solutions Given its extensive benefits, citizen development is a strategy many businesses are eager to adopt. Salesforce provides a powerful platform to effectively harness citizen development. Salesforce’s platform caters to both professional and citizen developers, offering a comprehensive suite of user-friendly tools for building applications and managing workflows. With built-in safeguards for data security and regulatory compliance, Salesforce for Public Sector and Tribal Governments ensures a smooth and secure citizen development process. Their clear deployment roadmap and thorough training programs equip businesses for success in their citizen development journey. 4. Partnering with Tectonic for Public Sector and Tribal Government Solutions Consider Tectonic as your trusted partner for PSS solutions. Tectonic is a distinguished provider of technology solutions with extensive expertise in Salesforce and process management. With a proven track record of successful projects, Tectonic has earned the trust of clients globally. Tectonic maintains a close partnership with Salesforce, ensuring a deep understanding of its advanced features, including process automation. As a Salesforce partner, Tectonic keeps clients updated on the latest advancements, delivering cutting-edge solutions tailored to their specific needs. By selecting Tectonic as your implementation partner for public sector Salesforce, you benefit from their vast experience and specialized knowledge. Tectonic provides a dedicated public sector team that excels in implementing secure and efficient solutions, working closely with our clients to address their unique challenges. Tectonic offers a comprehensive range of services, from initial implementation to ongoing support and maintenance. Their offerings include process modeling, application design, automation implementation, and roles management. With Tectonic’s expertise, you can ensure seamless integration of automation into your pss projects. To learn more about Tectonic’s public sector services, visit our services page, where you can explore their offerings, including Salesforce Managed Services. Tectonic’s Managed Services provide full support to ensure your public sector environment runs smoothly, covering automation management, data governance, and performance optimization. 5. Final Thoughts While citizen development presents both advantages and challenges, the benefits largely outweigh the potential drawbacks. Although there are concerns about data security and the need for proper governance, the positive impact of citizen development makes it a vital component of the digital transformation narrative. Successful implementation hinges on selecting the right platform and tools that align with your business model and workflow needs. Salesforce Public Sector Solution excels in this regard, offering a user-friendly suite of tools with a clear roadmap for deployment and top-notch support. Brining your public sector tech into the 21st century is an imperative. To fully realize the benefits of citizen development, businesses must strike a balance between empowerment and control. Establishing an environment that fosters innovation and efficiency, while also implementing a governance structure to mitigate risks, is essential. With careful planning, the right tools, and a culture of collaboration, the rewards of citizen development can be substantial. Whether you’re looking to enhance speed and agility, optimize costs, or cultivate a culture of innovation, citizen development offers a promising pathway forward. Embrace citizen development in Salesforce PSS, and set your business on the road to success. If you have any questions about implementing Salesforce Public Sector Solutions and its benefits, feel free to contact us to discuss your project. 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

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September 6, 2024in Data, Salesforce Development Services, Salesforce Public Sector Solutions, Technology
Salesforce to Acquire Own
06Sep

Salesforce to Acquire Own

Salesforce is set to acquire data protection and management vendor Own Co. for approximately $1.9 billion in cash. This move aligns with Salesforce’s ongoing investment in artificial intelligence (AI) and its efforts to bolster cybersecurity amidst rising data security concerns.  The San Francisco-based CRM giant expects to finalize the acquisition of Own by the fourth quarter of its fiscal year 2025, according to a company statement. Own, formerly known as OwnBackup, touts itself as the leading cloud data protection platform for Salesforce, serving around 7,000 customers with services such as data archiving, security, and analytics. He highlighted that Own’s expertise would enhance Salesforce’s data protection and management capabilities, reinforcing the company’s commitment to secure, end-to-end solutions. Sam Gutmann, CEO of Own, echoed the sentiment, stating that the acquisition would allow Own and Salesforce to drive innovation and secure data, particularly in highly regulated industries. Gutmann, who previously founded Intronis, has led Own’s growth since its establishment in 2015, with backing from investors like BlackRock and Salesforce Ventures. The acquisition is expected to strengthen Salesforce’s existing offerings, such as Backup, Shield, and Data Mask. Own, known for its data resilience platform, has raised over 0 million in funding and partnered with major tech players like ServiceNow and Microsoft Dynamics 365. The deal comes shortly after Salesforce announced plans to acquire Tenyx, an AI-powered voice agent startup, as part of its broader AI-driven strategy. Salesforce has shifted focus from larger acquisitions in recent years, prioritizing shareholder returns. However, this purchase reflects the company’s strategic shift towards enhancing its AI and data security solutions to maintain growth momentum. Salesforce anticipates that the Own deal will be accretive to free cash flow starting in the second year after the transaction closes, without affecting its current capital return program. This acquisition underscores Salesforce’s evolving focus on data protection, especially as AI adoption grows and data security becomes increasingly important. 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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September 6, 2024in Einstein 1 Platform
Data Quality Critical
06Sep

Data Quality Critical

Data quality has never been more critical, and it’s only set to grow in importance with each passing year. The reason? The rise of AI—particularly generative AI. Generative AI offers transformative benefits, from vastly improved efficiency to the broader application of data in decision-making. But these advllucantages hinge on the quality of data feeding the AI. For enterprises to fully capitalize on generative AI, the data driving models and applications must be accurate. If the data is flawed, so are the AI’s outputs. Generative AI models require vast amounts of data to produce accurate responses. Their outputs aren’t based on isolated data points but on aggregated data. Even if the data is high-quality, an insufficient volume could result in an incorrect output, known as an AI hallucination. With so much data needed, automating data pipelines is essential. However, with automation comes the challenge: humans can’t monitor every data point along the pipeline. That makes it imperative to ensure data quality from the outset and to implement output checks along the way, as noted by David Menninger, an analyst at ISG’s Ventana Research. Ignoring data quality when deploying generative AI can lead to not just inaccuracies but biased or even offensive outcomes. “As we’re deploying more and more generative AI, if you’re not paying attention to data quality, you run the risks of toxicity, of bias,” Menninger warns. “You’ve got to curate your data before training the models and do some post-processing to ensure the quality of the results.” Enterprises are increasingly recognizing this, with leaders like Saurabh Abhyankar, chief product officer at MicroStrategy, and Madhukar Kumar, chief marketing officer at SingleStore, noting the heightened emphasis on data quality, not just in terms of accuracy but also security and transparency. The rise of generative AI is driving this urgency. Generative AI’s potential to lower barriers to analytics and broaden access to data has made it a game-changer. Traditional analytics tools have been difficult to master, often requiring coding skills and data literacy training. Despite efforts to simplify these tools, widespread adoption has been limited. Generative AI, however, changes the game by enabling natural language interactions, making it easier for employees to engage with data and derive insights. With AI-powered tools, the efficiency gains are undeniable. Generative AI can take on repetitive tasks, generate code, create data pipelines, and even document processes, allowing human workers to focus on higher-level tasks. Abhyankar notes that this could be as transformational for knowledge workers as the industrial revolution was for manual labor. However, this potential is only achievable with high-quality data. Without it, AI-driven decision-making at scale could lead to ethical issues, misinformed actions, and significant consequences, especially when it comes to individual-level decisions like credit approvals or healthcare outcomes. Ensuring data quality is challenging, but necessary. Organizations can use AI-powered tools to monitor data quality, detect irregularities, and alert users to potential issues. However, as advanced as AI becomes, human oversight remains critical. A hybrid approach, where technology augments human expertise, is essential for ensuring that AI models and applications deliver reliable outputs. As Kumar of SingleStore emphasizes, “Hybrid means human plus AI. There are things AI is really good at, like repetition and automation, but when it comes to quality, humans are still better because they have more context.” Ultimately, while AI offers unprecedented opportunities, it’s clear that data quality is the foundation. Without it, the risks are too great, and the potential benefits could turn into unintended consequences. 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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September 6, 2024in Data, Enterprise, Generative AI, Salesforce, Technology
Exploring Large Action Models
05Sep

Exploring Large Action Models

Exploring Large Action Models (LAMs) for Automated Workflow Processes While large language models (LLMs) are effective in generating text and media, Large Action Models (LAMs) push beyond simple generation—they perform complex tasks autonomously. Imagine an AI that not only generates content but also takes direct actions in workflows, such as managing customer relationship management (CRM) tasks, sending emails, or making real-time decisions. LAMs are engineered to execute tasks across various environments by seamlessly integrating with tools, data, and systems. They adapt to user commands, making them ideal for applications in industries like marketing, customer service, and beyond. Key Capabilities of LAMs A standout feature of LAMs is their ability to perform function-calling tasks, such as selecting the appropriate APIs to meet user requirements. Salesforce’s xLAM models are designed to optimize these tasks, achieving high performance with lower resource demands—ideal for both mobile applications and high-performance environments. The fc series models are specifically tuned for function-calling, enabling fast, precise, and structured responses by selecting the best APIs based on input queries. Practical Examples Using Salesforce LAMs In this article, we’ll explore: Implementation: Setting Up the Model and API Start by installing the necessary libraries: pythonCopy code! pip install transformers==4.41.0 datasets==2.19.1 tokenizers==0.19.1 flask==2.2.5 Next, load the xLAM model and tokenizer: pythonCopy codeimport json import torch from transformers import AutoModelForCausalLM, AutoTokenizer model_name = “Salesforce/xLAM-7b-fc-r” model = AutoModelForCausalLM.from_pretrained(model_name, device_map=”auto”, torch_dtype=”auto”, trust_remote_code=True) tokenizer = AutoTokenizer.from_pretrained(model_name) Now, define instructions and available functions. Task Instructions: The model will use function calls where applicable, based on user questions and available tools. Format Example: jsonCopy code{ “tool_calls”: [ {“name”: “func_name1”, “arguments”: {“argument1”: “value1”, “argument2”: “value2”}} ] } Define available APIs: pythonCopy codeget_weather_api = { “name”: “get_weather”, “description”: “Retrieve weather details”, “parameters”: {“location”: “string”, “unit”: “string”} } search_api = { “name”: “search”, “description”: “Search for online information”, “parameters”: {“query”: “string”} } Creating Flask APIs for Business Logic We can use Flask to create APIs to replicate business processes. pythonCopy codefrom flask import Flask, request, jsonify app = Flask(__name__) @app.route(“/customer”, methods=[‘GET’]) def get_customer(): customer_id = request.args.get(‘customer_id’) # Return dummy customer data return jsonify({“customer_id”: customer_id, “status”: “active”}) @app.route(“/send_email”, methods=[‘GET’]) def send_email(): email = request.args.get(’email’) # Return dummy response for email send status return jsonify({“status”: “sent”}) Testing the LAM Model and Flask APIs Define queries to test LAM’s function-calling capabilities: pythonCopy codequery = “What’s the weather like in New York in fahrenheit?” print(custom_func_def(query)) # Expected: {“tool_calls”: [{“name”: “get_weather”, “arguments”: {“location”: “New York”, “unit”: “fahrenheit”}}]} Function-Calling Models in Action Using base_call_api, LAMs can determine the correct API to call and manage workflow processes autonomously. pythonCopy codedef base_call_api(query): “””Calls APIs based on LAM recommendations.””” base_url = “http://localhost:5000/” json_response = json.loads(custom_func_def(query)) api_url = json_response[“tool_calls”][0][“name”] params = json_response[“tool_calls”][0][“arguments”] response = requests.get(base_url + api_url, params=params) return response.json() With LAMs, businesses can automate and streamline tasks in complex workflows, maximizing efficiency and empowering teams to focus on strategic initiatives. 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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September 5, 2024in Data, Salesforce, Technology, Third Party Apps

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