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Generative AI Overview

Generative AI Overview

Editor’s Note: AI Cloud, Einstein GPT, and other cloud GPT products are now Einstein. For the latest on Salesforce Einstein The Rise of Generative AI: What It Means for Business and CRM Generative artificial intelligence (AI) made headlines in late 2022, sparking widespread curiosity and questions about its potential impact on various industries. What is Generative AI? Generative AI is a technology that creates new content—such as poetry, emails, images, or music—based on a set of input data. Unlike traditional AI, which focuses on classifying or predicting, generative AI can produce novel content with a human-like understanding of language, as noted by Salesforce Chief Scientist Silvio Savarese. However, successful generative AI depends on the quality of the input data. “AI is only as good as the data you give it, and you must ensure that datasets are representative,” emphasizes Paula Goldman, Salesforce’s Chief Ethical and Humane Use Officer. How Does Generative AI Work? Generative AI can be developed using several deep learning approaches, including: Other methods include Variational Autoencoders (VAEs) and Neural Radiance Fields (NeRFs), which generate new data or create 2D and 3D images based on sample data. Generative AI and Business Generative AI has captured the attention of global business leaders. A recent Salesforce survey found that 67% of IT leaders are focusing on generative AI in the next 18 months, with 33% considering it a top priority. Salesforce has long been exploring generative AI applications. For instance, CodeGen helps transform simple English prompts into executable code, and LAVIS makes language-vision AI accessible to researchers. More recently, Salesforce’s ProGen project demonstrated the creation of novel proteins using AI, potentially advancing medicine and treatment development. Ketan Karkhanis, Salesforce’s Executive VP and GM of Sales Cloud, highlights that generative AI benefits not just large enterprises but also small and medium-sized businesses (SMBs) by automating proposals, customer communications, and predictive sales modeling. Challenges and Ethical Considerations Despite its potential, generative AI poses risks, as noted by Paula Goldman and Kathy Baxter of Salesforce’s Ethical AI practice. They stress the importance of responsible innovation to ensure that generative AI is used safely and ethically. Accuracy in AI recommendations is crucial, and the authoritative tone of models like ChatGPT can sometimes lead to misleading results. Salesforce is committed to building trusted AI with embedded guardrails to prevent misuse. As generative AI evolves, it’s vital to balance its capabilities with ethical considerations, including its environmental impact. Generative AI can increase IT energy use, which 71% of IT leaders acknowledge. Generative AI at Salesforce Salesforce has integrated AI into its platform for years, with Einstein AI providing billions of daily predictions to enhance sales, service, and customer understanding. The recent launch of Einstein GPT, the world’s first generative AI for CRM, aims to transform how businesses interact with customers by automating content creation across various functions. Salesforce Ventures is also expanding its Generative AI Fund to $500 million, supporting AI startups and fostering responsible AI development. This expansion includes investments in companies like Anthropic and Cohere. As Salesforce continues to lead in AI innovation, the focus remains on creating technology that is inclusive, responsible, and sustainable, paving the way for the future of CRM and business. The Future of Business: AI-Powered Leadership and Decision-Making Tomorrow’s business landscape will be transformed by specialized, autonomous AI agents that will significantly change how companies are run. Future leaders will depend on these AI agents to support and enhance their teams, with AI chiefs of staff overseeing these agents and harnessing their capabilities. New AI-powered tools will bring businesses closer to their customers and enable faster, more informed decision-making. This shift is not just a trend—it’s backed by significant evidence. The Slack Workforce Index reveals a sevenfold increase in leaders seeking to integrate AI tools since September 2023. Additionally, Salesforce research shows that nearly 80% of global workers are open to an AI-driven future. While the pace of these changes may vary, it is clear that the future of work will look vastly different from today. According to the Slack Workforce Index, the number of leaders looking to integrate AI tools into their business has skyrocketed 7x since September 2023. Mick Costigan, VP, Salesforce Futures In the [still] early phases of a major technology shift, we tend to over-focus on the application of technology innovations to existing workflows. Such advances are important, but closing the imagination gap about the possible new shapes of work requires us to consider more than just technology. It requires us to think about people, both as the customers who react to new offerings and as the employees who are responsible for delivering them. Some will eagerly adopt new technology. Others will resist and drag their feet. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce on AI

Salesforce on AI

Marketing success hinges on delivering consistent, timely, and engaging content. According to the Salesforce State of Marketing report, 78% of high-performing marketers identify data as their most critical asset for creating cohesive customer journeys. Yet, only 49% report having a unified view of customer data sources. This disconnect highlights a significant challenge many marketing teams face in effectively leveraging their data. For organizations already invested in Salesforce, incorporating AI-driven business intelligence (BI) tools offers numerous benefits. These include reduced time to deliver insights, enhanced automation, increased innovation, improved agility, and cost savings. However, realizing these benefits depends on having high-quality data and robust data strategies. This insight explores AI-driven BI from a Salesforce perspective, highlighting its benefits, applications, and future trends. By understanding the potential of AI in BI, organizations can better harness their data to drive success and innovation. The Role of AI in Business Intelligence Integrating AI into BI systems elevates data analysis by offering deeper insights and predictive capabilities. Here’s how AI enhances BI: These examples demonstrate AI’s ability to improve BI systems by enhancing data accuracy, providing real-time insights, and improving forecasting. Salesforce’s AI Capabilities in BI Salesforce’s AI capabilities in BI are embodied in the versatile tool, Salesforce Einstein. Easily integrated with BI, Einstein automates tasks and delivers personalized insights. Companies using Einstein have reported a 20% increase in sales productivity. Here’s how Einstein can be utilized in various scenarios: These examples illustrate how Salesforce’s AI tools, particularly Einstein, can transform BI by automating routine tasks and delivering personalized insights, ultimately driving customer satisfaction and business growth. Future Trends in AI and BI The future of AI and BI promises even more advanced capabilities and innovations. As AI evolves, so too will the tools for BI. Here are some trends expected to emerge in the near future: These trends show that AI and BI are evolving rapidly. Companies that stay ahead of these developments will be well-positioned to leverage AI for greater innovation and efficiency. Next Steps AI-powered BI, especially with Salesforce, is transforming how businesses operate by providing deeper insights and better decision-making capabilities. To stay competitive and foster innovation, organizations must embrace AI. The quest is no longer just to be data-driven. It is to be data-decisioned. Here are some actionable steps: By taking these steps, businesses can fully leverage AI-driven BI and maintain a competitive edge in the fast-evolving digital playinf field of 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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AI All Grown Up

Generative AI Tools

One of the most significant use cases for generative AI in business is customer service and support. Most of us have likely experienced the frustration of dealing with traditional automated systems. However, today’s advanced AI, powered by large language models and natural language chatbots, is rapidly improving these interactions. While many still prefer human agents for complex or sensitive issues, AI is proving highly capable of handling routine inquiries efficiently. Here’s an overview of some of the top AI-powered tools for automating customer service. Although the human element will always be essential in customer experience, these tools free up human agents from repetitive tasks, allowing them to focus on more complex challenges requiring empathy and creativity. Cognigy Cognigy is an AI platform designed to automate customer service voice and chat channels. It goes beyond simply reading FAQ responses by delivering personalized, context-sensitive answers in multiple languages. Cognigy’s AI Copilot feature enhances human contact center workers by offering real-time AI assistance during interactions, making both fully automated and human-augmented support possible. IBM WatsonX Assistant IBM’s WatsonX Assistant helps businesses create AI-powered personal assistants to streamline tasks, including customer support. With its drag-and-drop configuration, companies can set up seamless self-service experiences. The platform uses retrieval-augmented generation (RAG) to ensure that responses are accurate and up-to-date, continuously improving as it learns from customer interactions. Salesforce Einstein Service Cloud Einstein Service Cloud, part of the Salesforce platform, automates routine and complex customer service tasks. Its AI-powered Agentforce bots manage “low-touch” interactions, while “high-touch” cases are overseen by human agents supported by AI. Fully customizable, Einstein ensures that responses align with your brand’s tone and voice, all while leveraging enterprise data securely. Zendesk AI Zendesk, a leader in customer support, integrates generative AI to boost its service offerings. By using machine learning and natural language processing, Zendesk understands customer sentiment and intent, generates personalized responses, and automatically routes inquiries to the most suitable agent—be it human or machine. It also provides human agents with real-time guidance on resolving issues efficiently. Ada Ada is a conversational AI platform built for large-scale customer service automation. Its no-code interface allows businesses to create custom bots, reducing the cost of handling inquiries by up to 78% per ticket. By integrating domain-specific data, Ada helps improve both support efficiency and customer experience across omnichannel support environments. More AI Tools for Customer Service There are numerous other AI tools designed to enhance automated customer support: While AI tools are transforming customer service, the key lies in using them to complement human agents, allowing for a balance of efficiency and personalized care. 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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Data Cloud and Genpact

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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Salesforce Data Cloud Pioneer

Salesforce Data Cloud Pioneer

While many organizations are still building their data platforms, Salesforce Data Cloud Pioneer has made a significant leap forward. By seamlessly incorporating metadata integration, Salesforce has transformed the modern data stack into a comprehensive application platform known as the Einstein 1 Platform. Led by Muralidhar Krishnaprasad, executive vice president of engineering at Salesforce, the Einstein 1 Platform is built on the company’s metadata framework. This platform harmonizes metadata and integrates it with AI and automation, marking a new era of data utilization. The Einstein 1 Platform: Innovations and Capabilities Salesforce’s goal with the Einstein 1 Platform is to empower all business users—salespeople, service engineers, marketers, and analysts—to access, use, and act on all their data, regardless of its location, according to Krishnaprasad. The open, extensible platform not only unlocks trapped data but also equips organizations with generative AI functionality, enabling personalized experiences for employees and customers. “Analytics is very important to know how your business is doing, but you also want to make sure all that data and insights are actionable,” Krishnaprasad said. “Our goal is to blend AI, automation, and analytics together, with the metadata layer being the secret sauce.” Salesforce Data Cloud Pioneer In a conversation with George Gilbert, senior analyst at theCUBE Research, Krishnaprasad discussed the platform’s metadata integration, open-API technology, and key features. They explored how its extensibility and interoperability enhance usability across various data formats and sources. Metadata Integration: Accommodating Any IT Environment The Einstein 1 Platform is built on Trino, the federated open-source query engine, and Spark for data processing. It offers a rich set of connectors and an open, extensible environment, enabling organizations to share data between warehouses, lake houses, and other systems. “We use a hyper-engine for sub-second response times in Tableau and other data explorations,” Krishnaprasad explained. “This in-memory overlap engine ensures efficient data processing.” The platform supports various machine learning options and allows users to integrate their own large language models. Whether using Salesforce Einstein, Databricks, Vertex, SageMaker, or other solutions, users can operate without copying data. The platform includes three levels of extensibility, enabling organizations to standardize and extend their customer journey models. Users can start with basic reference models, customize them, and then generate insights, including AI-driven insights. Finally, they can introduce their own functions or triggers to act on these insights. The platform continuously performs unification, allowing users to create different unified graphs based on their needs. “We’re a multimodal system, considering your entire customer journey,” Krishnaprasad said. “We provide flexibility at all levels of the stack to create the right experience for your business.” The Triad of AI, Automation, and Analytics The platform’s foundation ingests, harmonizes, and unifies data, resulting in a standardized metadata model that offers a 360-degree view of customer interactions. This approach unlocks siloed data, much of which is in unstructured forms like conversations, documents, emails, audio, and video. “What we’ve done with this customer 360-degree model is to use unified data to generate insights and make these accessible across application surfaces, enabling reactions to these insights,” Krishnaprasad said. “This unlocks a comprehensive customer journey.” For instance, when a customer views an ad and visits the website, salespeople know what they’re interested in, service personnel understand their concerns, and analysts have the information needed for business insights. These capabilities enhance customer engagement. “Couple this with generative AI, and we enable a lot of self-service,” Krishnaprasad added. “We aim to provide accurate answers, elevating data to create a unified model and powering a unified experience across the entire customer journey.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce Workday Partnership

Salesforce Workday Partnership

Salesforce and Workday Partner to Launch AI-Powered Employee Service Agent Salesforce (NYSE: CRM), the leading AI CRM platform, and Workday, Inc. (NASDAQ: WDAY), a leader in enterprise cloud applications for finance and HR, today announced a strategic partnership to develop a new AI-powered employee service agent. This solution will enhance employee experiences by automating routine tasks, providing personalized support, and delivering data-driven insights across Salesforce and Workday platforms. A Unified Data Foundation for Enhanced Employee Services The partnership will integrate HR and financial data from Workday with CRM data from Salesforce, creating a unified data foundation. This integration will enable the development of AI-driven use cases that increase productivity, reduce costs, and improve the employee experience. A key feature will be the seamless incorporation of Workday into Slack, allowing for enhanced automation and collaboration around HR and financial records, using AI. The new AI employee service agent, built on Salesforce’s Agentforce Platform and Einstein AI, alongside Workday AI, will cater to various employee service needs, such as onboarding, health benefits management, and career development. This agent will utilize a company’s data to interact with employees in natural language, offering personalized support and executing tasks based on trusted business rules and permissions. Enhancing Employee and Customer Success “The AI opportunity lies in augmenting employees and delivering exceptional customer experiences. Our collaboration with Workday will empower businesses to create remarkable experiences using generative and autonomous AI, allowing employees to efficiently find answers, learn new skills, solve problems, and take actions.” Marc Benioff, Chair and CEO of Salesforce Carl Eschenbach, CEO of Workday, highlighted the integration’s benefits: “By combining our platforms, data, and AI capabilities, we empower customers to deliver unmatched AI-powered employee experiences, leading to happier customers and substantial business value.” Key Features of the Partnership Benefits for Employees and Employers For Employees: For Employers: Sal Companieh, Chief Digital and Information Officer at Cushman & Wakefield, noted the strategic advantage: “The integration of Workday and Salesforce will streamline workflows and deliver more personalized, AI-powered employee experiences, significantly enhancing our operational efficiency.” “The shared data foundation between Workday and Salesforce will enable these partners to deliver transformative AI capabilities, enhancing employee experiences and driving business performance.” R “Ray” Wang, CEO of Constellation Research, Inc. About Workday Workday is a leading enterprise platform that helps organizations manage their most important assets – their people and money. The Workday platform is built with AI at the core to help customers elevate people, supercharge work, and move their business forever forward. Workday is used by more than 10,500 organizations around the world and across industries – from medium-sized businesses to more than 60% of the Fortune 500. For more information about Workday, visit workday.com. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Einstein Code Generation and Amazon SageMaker

Einstein Code Generation and Amazon SageMaker

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

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Can We Customize Manufacturing Cloud For Our Business

Can We Customize Manufacturing Cloud For Our Business?

Yes, Salesforce Manufacturing Cloud Can Be Customized to Meet Your Business Needs Salesforce Manufacturing Cloud is designed to be highly customizable, allowing manufacturing organizations to tailor it to their unique business requirements. Whether it’s adapting the platform to fit specific workflows, integrating with third-party systems, or enhancing reporting capabilities, Salesforce provides robust customization options to meet the specific needs of manufacturers. Here are key ways Salesforce Manufacturing Cloud can be customized: 1. Custom Data Models and Objects Salesforce allows you to create custom objects and fields to track data beyond the standard model. This flexibility enables businesses to manage unique production metrics or product configurations seamlessly within the platform. Customization Options: 2. Sales Agreement Customization Sales Agreements in Salesforce Manufacturing Cloud can be tailored to reflect your business’s specific contract terms and pricing models. You can adjust agreement structures, including the customization of terms, conditions, and rebate tracking. Customization Options: 3. Custom Workflows and Automation Salesforce offers tools like Flow Builder and Process Builder, allowing manufacturers to automate routine tasks and create custom workflows that streamline operations. Customization Options: 4. Integration with Third-Party Systems Salesforce Manufacturing Cloud can integrate seamlessly with ERP systems (like SAP or Oracle), inventory management platforms, and IoT devices to ensure a smooth data flow across departments. Integration Options: 5. Custom Reports and Dashboards With Salesforce’s robust reporting tools, you can create custom reports and dashboards that provide real-time insights into key performance indicators (KPIs) relevant to your manufacturing operations. Customization Options: 6. Custom User Interfaces Salesforce Lightning allows you to customize user interfaces to meet the needs of different roles within your organization, such as production managers or sales teams. This ensures users have quick access to relevant data. Customization Options: Conclusion Salesforce Manufacturing Cloud provides a wide range of customization options to suit the unique needs of your manufacturing business. Whether it’s adjusting data models, automating processes, or integrating with external systems, Manufacturing Cloud can be tailored to meet your operational goals. By leveraging these customizations, manufacturers can optimize their operations, improve data accuracy, and gain real-time insights to boost efficiency. If you need help customizing Salesforce Manufacturing Cloud, Service Cloud, or Sales Cloud for your business, our Salesforce Manufacturing Cloud Services team is here to assist. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce Tiny Giant LLM

Salesforce Tiny Giant LLM

‘On-device Agentic AI is Here!’: Salesforce Announces the ‘Tiny Giant’ LLM Salesforce CEO Marc Benioff is excited about the company’s latest innovation in AI, introducing the ‘Tiny Giant’ LLM, which he claims is the world’s top-performing “micro-model” for function-calling. Salesforce’s new slimline “Tiny Giant” LLM reportedly outperforms larger models, marking a significant advancement in on-device AI. According to a paper published on Arxiv by Salesforce’s AI Research department, the xLAM-7B LLM model ranked sixth among 46 models, including those from OpenAI and Google, in a competition testing function-calling (execution of tasks or functions through API calls). The xLAM-7B LLM was trained on just seven billion parameters, a small fraction compared to the 1.7 trillion parameters rumored to be used by GPT-4. However, Salesforce highlights the xLAM-1B, a smaller model, as its true star. Despite being trained on just one billion parameters, the xLAM-1B model finished 24th, surpassing GPT-3.5-Turbo and Claude-3 Haiku in performance. CEO Marc Benioff proudly shared these results on X (formerly Twitter), stating: “Meet Salesforce Einstein ‘Tiny Giant.’ Our 1B parameter model xLAM-1B is now the best micro-model for function-calling, outperforming models 7x its size… On-device agentic AI is here. Congrats Salesforce Research!” Salesforce’s research emphasizes that function-calling agents represent a significant advancement in AI and LLMs. Models like GPT-4, Gemini, and Mistral already execute API calls based on natural language prompts, enabling dynamic interactions with various digital services and applications. While many popular models are large and resource-intensive, requiring cloud data centers and extensive infrastructure, Salesforce’s new models demonstrate that smaller, more efficient models can achieve state-of-the-art performance. To test function-calling LLMs, Salesforce developed APIGen, an “Automated Pipeline for Generating verifiable and diverse function-calling datasets,” to synthesize data for AI training. Salesforce’s findings indicate that models trained on relatively small datasets can outperform those trained on larger datasets. “Models trained with our curated datasets, even with only seven billion parameters, can achieve state-of-the-art performance… outperforming multiple GPT-4 models,” the paper states. The ultimate goal is to create agentic AI models capable of function-calling and task execution on devices, minimizing the need for extensive external infrastructure and enabling self-sufficient operations. Dr. Eli David, Co-Founder of the cybersecurity firm Deep Instinct, commented on X, “Smaller, more efficient models are the way to go for widespread deployment of LLMs.” 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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Democratize Data with Einstein Copilot for Tableau

Democratize Data with Einstein Copilot for Tableau

Most workers today recognize the importance of rich data analytics in their jobs. However, 33% struggle to understand and generate insights from data. To address this, Salesforce has introduced Einstein Copilot for Tableau, which allows users of all skill levels to create complex data visualizations without extensive learning or coding. Democratize Data with Einstein Copilot for Tableau. Launched in April 2024, the beta version of this AI assistant features a user-friendly interface that simplifies the process with questions or simple commands. This facilitates the quick creation of comprehensive data presentations, including reports, dashboards, and various charts. Democratize Data with Einstein Copilot for Tableau Einstein Copilot for Tableau leverages a combination of AI technologies—natural language processing (NLP), machine learning (ML), and generative AI—to provide actionable insights. NLP enables conversational and intuitive interactions, while ML models process user queries and analyze data. Generative AI drives cognitive reasoning, planning, and creates insights, recommendations, and diagrams based on user inputs. By integrating with Tableau Cloud, Einstein Copilot accesses historical proprietary data, enables advanced data analysis, and translates user intent into actionable insights. It relies on Tableau’s analytics infrastructure to execute code and displays results through user-friendly visualizations and dashboards. Additionally, the Einstein Trust Layer secures and protects private data in Einstein Copilot. It authorizes inbound requests, ensuring users have necessary permissions to access specific data and safeguards model outputs to prevent the disclosure of confidential information. How Einstein Copilot for Tableau Transforms Requests into Insights To understand how Einstein Copilot for Tableau turns requests into actionable insights, let’s walk through each step of the interaction process: Einstein Copilot for Tableau democratizes access to data analytics, enabling all users to harness the power of data without needing extensive technical knowledge. 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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Five9 Salesforce AI Integration

Five9 Salesforce AI Integration

Five9 and Salesforce Enhance AI-Powered Solutions for Superior Customer Experiences Five9 (NASDAQ: FIVN), a provider of the Intelligent CX Platform, today announced the next step in its collaboration with Salesforce. Five9 Salesforce AI Integration. This partnership aims to deliver AI-powered solutions to enhance customer experiences (CX) in contact centers. The latest release, Five9 for Service Cloud Voice with Partner Telephony, integrates Salesforce Einstein with Five9’s suite of AI solutions. This empowers agents to better service customer requests, improves management’s understanding of contact center operations, and delivers customer resolutions that exceed expectations. Using Five9’s open APIs and Five9 TranscriptStream, the Einstein AI engine identifies opportunities to provide real-time solutions for agents, prompting ‘Next Best Action’ guidance. The solution also offers real-time transcription of customer conversations, ensures call recordings’ accuracy and relevance, and integrates with Salesforce Einstein Conversation Insights to enhance conversation intelligence. “Five9 understands the power of elevating the customer experience through innovative technology and seamless integrations,” said Dan Burkland, President of Five9. “Our collaboration with Salesforce pushes the boundaries of what is possible. Infusing Einstein’s AI insights into the contact center and CRM eliminates repetitive tasks while guiding agents with the next best actions to help them be more effective.” A Long-Standing Partnership The Salesforce-Five9 collaboration, now over 15 years strong, recently introduced Five9 call dispositions for agents within the Salesforce Omni-Channel widget or Voice Call page. This allows organizations to automatically update call dispositions in the Five9 call database, ensuring accurate reporting across the integration. Both companies are meeting the growing demand for AI solutions to enhance customer engagement throughout the customer journey. “Five9’s deeper integration with Salesforce Einstein offers a new level of choice for customers seeking AI capabilities that best match their contact center needs and existing technology investments,” said Sheila McGee-Smith, President & Principal Analyst at McGee-Smith Analytics. “Coupled with features like Five9 TranscriptStream, organizations can significantly reduce an agent’s workload while enhancing the customer’s overall experience. This next step in the Salesforce-Five9 relationship demonstrates each company’s commitment to their joint customer base, enabling them to leverage the latest AI innovations easily.” “Service Cloud Voice with Five9 uses AI to deliver a better customer experience,” said Ryan Nichols, Chief Product Officer of Service Cloud, Salesforce. “Our collaboration focuses on more than just a ‘single pane of glass’– we’re bringing together customer data, knowledge, and real-time conversation transcripts to help make agents more productive and delight customers.” Availability and Further Information These new enhancements to Five9 for Service Cloud Voice with Partner Telephony will be available starting June 30. For a deeper look into the Five9 integration with Service Cloud Voice and to explore common use cases, register for the webinar “Unlock Efficiency with the Power of AI: Five9 and Salesforce Service Cloud Voice” on Tuesday, July 23. An on-demand playback of the December 2023 Five9 and Salesforce joint webinar is also available, covering topics such as using data for personalization, best practices for leveraging engagement data to improve experiences, and how companies can become more customer-centric. Salesforce, Einstein, and other related marks are trademarks of Salesforce, Inc. 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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Trust Einstein Copilot for Tableau

Trust Einstein Copilot for Tableau

Are you prepared to utilize the capabilities of Einstein Copilot to expand your organization’s analytical advantages? This robust tool facilitates data exploration, insights generation, and visualization development at an unprecedented pace. However, before immersing yourself in its capabilities, it’s crucial to grasp how Einstein Copilot upholds Tableau and Salesforce’s core value: Trust. Let’s discover how the Einstein Trust Layer safeguards your data, ensures result accuracy, and facilitates auditing, addressing common questions and concerns raised by our customers.Trust Einstein Copilot for Tableau. What is Einstein Copilot for Tableau? Using generative AI and statistical analysis, Einstein Copilot for Tableau is able to understand the context of your data to create and suggest relevant business questions to help kickstart your analysis. A smart, conversational assistant for Tableau users, Einstein Copilot for Tableau automates data curation—the organization and integration of data collected from various sources—by generating calculations and metadata descriptions. Einstein Copilot for Tableau can fill data gaps and enhance analysis by creating synthetic datasets where real data is limited. Einstein Copilot helps you anticipate outcomes with predictive analytics that simulate diverse scenarios and uncover hidden correlations. Additionally, generative models can increase data privacy by producing non-traceable data for analysis.  Fulfilling the promise of generative AI, Einstein Copilot for Tableau presents an efficient, insightful, and ethical approach to data analytics. Think of it as an intelligent assistant integrated into the Tableau suite of products to make everyone successful in their analysis workflow—whether they’re an experienced data analyst or a data explorer. As your intelligent analytics AI assistant, Einstein Copilot for Tableau guides you through the process of creating data visualizations in Tableau by assisting you with recommended questions, conversational data exploration, guided calculation creation, and more. Understanding the Einstein Trust Layer The Einstein Trust Layer constitutes a secure AI architecture embedded within the Salesforce platform. Comprising agreements, security technology, and data privacy controls, it ensures the safety of your data while exploring generative AI solutions. Built upon the Einstein Trust Layer, Einstein Copilot for Tableau and other Tableau AI features inherit its security, governance, and Trust capabilities. The Einstein Trust Layer is a secure AI architecture, built into the Salesforce platform. It is a set of agreements, security technology, and data and privacy controls used to keep your company safe while you explore generative AI solutions. Tableau has been on the journey to help people see and understand their data for over two decades. Thanks to data analysts, this mission has been a success and will continue to be a success. Data analysts are the backbone of organizations that champion data culture, capture business requirements, prep data, and create data content for end users. Data Access and Privacy Who Accesses Your Data? A primary concern among our customers revolves around data access. Rest assured, the Einstein Trust Layer enforces strict policies to safeguard your organization’s data. Third-party LLM providers, including Open AI and Azure Open AI, adhere to a zero data retention policy. This means that data sent to LLMs isn’t stored; once processed, both the prompt and response are promptly forgotten. Additionally, each Einstein Copilot for Tableau customer receives their own Data Cloud instance, securely storing prompts and responses for auditing purposes. Data Residency and Access Control Einstein Copilot for Tableau respects permissions, row-level security, and data policies within Tableau Cloud, ensuring that only authorized personnel within your organization access specific data. Whether using Einstein Copilot or not, data access is restricted based on organizational roles and permissions. Data Handling and Processing Data Sent Outside of Tableau Cloud Site Einstein Copilot for Tableau operates within the confines of your Tableau site, scanning connected data sources to create a summary context. This summarized data is sent to third-party LLM providers for vectorization, enabling accurate interpretation of user queries. Importantly, the zero data retention policy ensures that summarized data is forgotten post-vectorization. Personally Identifiable Information (PII) Data To enhance data privacy, Einstein Copilot for Tableau employs data masking for PII data. This technique replaces sensitive information with placeholder text, ensuring privacy without sacrificing context. While our detection models strive for accuracy, continuous evaluation and refinement are paramount to maintain trust. Result Trustworthiness Ensuring Safe and Accurate Results Einstein Copilot for Tableau employs Toxicity Confidence Scoring to identify harmful inputs and responses. By combining rule-based filters and AI models, potentially harmful content is filtered and flagged for review. Furthermore, accuracy benchmarks ensure that generated results align closely with human-authored ones, bolstering trust in the platform. Future Trust Enhancements Trust remains an ongoing focus for our teams. Initiatives such as a BYO LLM solution and improved disambiguation capabilities are underway to further enhance trustworthiness. Continuous feedback, testing, and iteration drive our efforts to maintain your trust in Einstein Copilot for Tableau and the Einstein Trust Layer. Data analysis and data-driven decision-making have been part of the vocabulary in organizations over the years. And, while data analysis is one of the most in-demand tech skills sought by employers today, not everyone in an organization has “analyst” in their job title—myself included. Yet, so many of us use data daily to make informed decisions. The rise of generative AI presents a significant opportunity for us to bring transformative benefits to analytics. Businesses are eager to embrace generative AI because it can help save time, provide faster insights, and empower analysts to be even more productive with an AI assistant—freeing analysts to focus on delivering high-quality, data-driven insights. Is Tableau replacing Einstein analytics? Einstein Analytics has a new name. Say hello to Tableau CRM. Everything about how it works stays the same, just with that snazzy new name. When Tableau joined the Salesforce family, we brought together analytics capabilities of incredible depth and power. What is the difference between Einstein analytics and Tableau? If you’re only planning on analyzing Salesforce data, Einstein Analytics would probably make the most sense for you. However, if you need to analyze information that is coming from all over the place, Tableau will give your users more options. Tableau GPT infuses automation in every part of analytics – from preparation to communicating

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Einstein Personalization and Copilots

Einstein Personalization and Copilots

Salesforce launched a suite of new generative AI products at Connections in Chicago, including new Einstein Copilots for marketers and merchants, and Einstein Personalization. Einstein Personalization and Copilots To gain insights into these products and Salesforce’s evolving architecture, Bobby Jania, CMO of Marketing Cloud was interviewed. Salesforce’s Evolving Architecture Salesforce has a knack for introducing new names for its platforms and products, sometimes causing confusion about whether something is entirely new or simply rebranded. Reporters sought clarification on the Einstein 1 platform and its relationship to Salesforce Data Cloud. “Data Cloud is built on the Einstein 1 platform,” Jania explained. “Einstein 1 encompasses the entire Salesforce platform, including products like Sales Cloud and Service Cloud, continuing the original multi-tenant cloud concept.” Data Cloud, developed natively on Einstein 1, was the first product built on Hyperforce, Salesforce’s new cloud infrastructure. “From the start, Data Cloud has been able to connect to and read anything within Sales Cloud, Service Cloud, etc. Additionally, it can now handle both structured and unstructured data.” This marks significant progress from a few years ago when Salesforce’s platform comprised various acquisitions (like ExactTarget) that didn’t seamlessly integrate. Previously, data had to be moved between products, often resulting in duplicates. Now, Data Cloud serves as the central repository, with applications like Tableau, Commerce Cloud, Service Cloud, and Marketing Cloud all accessing the same operational customer profile without duplicating data. Salesforce customers can also import their own datasets into Data Cloud. “We wanted a federated data model,” Jania said. “If you’re using Snowflake, for example, we virtually sit on your data lake, providing value by forming comprehensive operational customer profiles.” Understanding Einstein Copilot “Copilot means having an assistant within the tool you’re using, contextually aware of your tasks and assisting you at every step,” Jania said. For marketers, this could start with a campaign brief created with Copilot’s help, identifying an audience, and developing content. “Einstein Studio is exciting because customers can create actions for Copilot that we hadn’t even envisioned.” Contrary to previous reports, there is only one Copilot, Einstein Copilot, with various use cases like marketing, merchants, and shoppers. “We use these names for clarity, but there’s just one Copilot. You can build your own use cases in addition to the ones we provide.” Marketers will need time to adapt to Copilot. “Adoption takes time,” Jania acknowledged. “This Connections event offers extensive hands-on training to help people use Data Cloud and these tools, beyond just demonstrations.” What’s New with Einstein Personalization Einstein Personalization is a real-time decision engine designed to choose the next best action or offer for customers. “What’s new is that it now runs natively on Data Cloud,” Jania explained. While many decision engines require a separate dataset, Einstein Personalization evaluates a customer holistically and recommends actions directly within Service Cloud, Sales Cloud, or Marketing Cloud. Ensuring Trust Connections presentations emphasized that while public LLMs like ChatGPT can be applied to customer data, none of this data is retained by the LLMs. This isn’t just a matter of agreements; it involves the Einstein Trust Layer. “All data passing through an LLM runs through our gateway. Personally identifiable information, such as credit card numbers or email addresses, is stripped out. The LLMs do not store the output; Salesforce retains it for auditing. Any output that returns through our gateway is logged, checked for toxicity, and only then is PII reinserted into the response. These measures ensure data safety beyond mere handshakes,” Jania 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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IBM Salesforce AI Partnership

IBM Salesforce AI Partnership

IBM and Salesforce Expand Partnership to Advance Open, Trusted AI and Data Ecosystems PR Newswire-IBM Salesforce AI Partnership ARMONK, N.Y. and SAN FRANCISCO, May 21, 2024 – IBM (NYSE: IBM) and Salesforce (NYSE: CRM) today announced an expanded strategic partnership designed to bring together IBM’s watsonx AI and Data Platform with the Salesforce Einstein 1 Platform. This collaboration aims to provide greater customer choice and flexibility in AI and data deployment, empowering teams to make data-driven decisions seamlessly. Key Highlights of the Expanded Partnership: 1. Enhanced Large Language Models for Generative AI: The IBM watsonx platform and IBM Granite series models will introduce more large language models (LLMs) to support generative AI use cases across the Salesforce Einstein 1 Platform. This integration will provide pre-built actions and prompts, enhancing AI capabilities for CRM solutions. 2. Zero Copy Data Integration: IBM joins the Salesforce Zero Copy Partner Network to enable secure, zero-copy data integration between IBM watsonx and Salesforce Data Cloud. This integration offers customers a cost-effective way to connect and leverage their data without the need to move it, ensuring seamless data access and actionability. 3. Commitment to Responsible AI: Salesforce has joined the AI Alliance, reinforcing its commitment to developing open, safe, and responsible AI. This collaboration aims to foster transparency and ethics in AI development, aligning with the AI Alliance’s mission to advance beneficial AI innovation. Integration Details: Large Language Model Flexibility: Organizations can deploy generative AI for CRM use cases with LLMs tailored to their business needs. Salesforce’s “Bring Your Own Large Language Model” strategy allows customers to integrate their LLMs with the watsonx.ai platform and Salesforce Einstein 1 Studio. This will provide access to IBM’s Granite series AI models and custom LLMs built on watsonx, enhancing AI-driven customer interactions. Industry-Specific Solutions: Together with IBM Consulting, Salesforce will offer industry-specific prompt templates and copilot actions in Einstein 1 Studio, starting with public sector use cases. These templates are designed to optimize both foundation and Granite models for various industries, including automotive, energy, financial services, and public sector. Bidirectional Data Integration: By joining the Salesforce Zero Copy Partner Network, IBM enables bidirectional data integration with Salesforce Data Cloud. This integration allows customers to access IBM data via watsonx.data within Salesforce Data Cloud, maintaining data security and minimizing risks. This approach simplifies data management, maximizing technology investments and ensuring comprehensive data accessibility for analytics and AI. Industry Impact: Ritika Gunnar, General Manager of Product Management, Data and AI at IBM, emphasized the importance of choosing the right foundation models for AI strategies, stating, “IBM and Salesforce are making it easier for clients to navigate the complex generative AI landscape by helping them select the right LLM for their business needs.” Rahul Auradkar, EVP & GM of United Data Services & Einstein at Salesforce, highlighted the benefits of the partnership, saying, “With bidirectional data integration, companies can harmonize all their data faster, fueling actionable insights that empower teams to make data-driven decisions and deliver integrated experiences across all customer touchpoints.” About IBM: IBM is a global leader in hybrid cloud and AI, providing consulting expertise to clients in over 175 countries. IBM’s innovations in AI, quantum computing, and industry-specific cloud solutions support digital transformations with a commitment to trust, transparency, and inclusivity. For more information, visit www.ibm.com. About Salesforce: Salesforce is the #1 AI CRM, helping companies connect with customers through CRM + AI + Data + Trust on one unified platform, Einstein 1. For more information, visit www.salesforce.com. For additional details on IBM Granite and the partnership with Salesforce, visit IBM Granite. Statements regarding IBM’s and Salesforce’s future directions are subject to change and represent goals and objectives only. 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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Einstein Generative AI Added to Service Cloud

Einstein Generative AI Added to Service Cloud

Salesforce to Enhance Service Cloud with New AI Tools and Broaden Automated Customer Conversations Salesforce is set to roll out more Einstein 1 generative AI tools for Service Cloud users in June and October. But the big news? More places to deploy automated customer conversations are on the way. Unified Conversations for WhatsApp and Line Yesterday, Salesforce unveiled Unified Conversations for WhatsApp. This feature automates bot responses to customer queries related to targeted marketing messages on the popular messaging app. And that’s not all—later this year, Salesforce plans to support Line, the widely used messaging app in Japan. These services leverage Salesforce’s Einstein 1 generative AI platform. The bots aggregate structured and unstructured CRM, product, service, and other data via Salesforce Data Cloud to generate personalized responses. The new features allow these conversations to be routed to the channels where a Salesforce user’s customers are most active online. Expanding Channel Support Salesforce also plans to introduce a “bring your own channel” connector to support digital channels not natively covered by the platform. Think TikTok, Discord, and South Korea’s KakaoTalk, said Ryan Nichols, chief product officer for Salesforce Service Cloud. “It’s about getting data from all your conversations with customers from Service Cloud into Data Cloud and using that to not just do a great job of delivering customer service, but actually growing your business,” Nichols explained. Conversation Mining and Revenue Opportunities Salesforce Einstein Conversation Mining, currently in beta, aggregates conversations across customer channels to surface insights on the topics where customers need help. The goal is to turn inbound customer service from a cost center into a revenue center—a dream that speakers and vendors at conferences like Dreamforce and ICMI have been floating for years. Traditionally, performance metrics such as time-to-answer and hold-time reduction have pushed agents to minimize call durations. However, the integration of generative AI could transform this dynamic. Constellation Research analyst Liz Miller, who has previously been skeptical, now sees generative AI as a potential game-changer. Armed with data, bots, and their copilot counterparts, agents could save time and access the right information to up-sell customers during service engagements. Nichols hinted that Salesforce is working on up-sell automation features for contact center service bots, which might be unveiled later this year. A Leap Forward for Contact Centers Copilot-type technologies for contact centers could be the breakthrough needed to enable human agents to generate revenue during service interactions. “Contact center leaders have been trying to etch out a space of strategic importance for themselves in the business that isn’t just ‘how do we get angry people off the phone?’” Miller said. Einstein Generative AI Added to Service Cloud Generative AI tools can eliminate the mundane, repetitive tasks that consume much of contact center agents’ time. Miller added, “If they no longer had to summarize the call, and they could actually go to the next call? [Generating revenue] sounds really big, and it sounds really ridiculous, but if we took all the garbage off of these people’s plates that no one wants to do, we give them an awful lot of time to actually be better mouthpieces for their organizations.” In short, Salesforce is gearing up to transform customer service into a more efficient, revenue-generating machine with a little help from generative AI. And who knows, maybe your next customer service bot will be better at upselling you than your favorite barista. 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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