Data Cloud Vector Database

09Jun

Gen AI Unleased With Vector Database

Salesforce Unveils Data Cloud Vector Database with GenAI Integration Salesforce has officially launched its Data Cloud Vector Database, leveraging GenAI to rapidly process a company’s vast collection of PDFs, emails, transcripts, online reviews, and other unstructured data. Gen AI Unleased With Vector Database. Rahul Auradkar, Executive Vice President and General Manager of Salesforce Unified Data Services and Einstein Units, highlighted the efficiency gains in a one-on-one briefing with InformationWeek. Auradkar demonstrated the new capabilities through a live demo, showcasing the potential of the Data Cloud Vector Database. Enhanced Efficiency and Data Utilization The new Data Cloud integrates with the Einstein 1 platform, combining unstructured and structured data for rapid analysis by sales, marketing, and customer service teams. This integration significantly enhances the accuracy of Einstein Copilot, Salesforce’s enterprise conversational AI assistant. Gen AI Unleased With Vector Database Auradkar demonstrated how a customer service query could retrieve multiple relevant results within seconds. This process, which typically takes hours of manual effort, now leverages unstructured data, which makes up 90% of customer data, to deliver swift and accurate results. “This advancement allows our customers to harness the full potential of 90% of their enterprise data—unstructured data that has been underutilized or siloed—to drive use cases, AI, automation, and analytics experiences across both structured and unstructured data,” Auradkar explained. Comprehensive Data Management Using Salesforce’s Einstein 1 platform, Data Cloud enables users to ingest, store, unify, index, and perform semantic queries on unstructured data across all applications. This data encompasses diverse unstructured content from websites, social media platforms, and other sources, resulting in more accurate outcomes and insights. Auradkar emphasized, “This represents an order of magnitude improvement in productivity and customer satisfaction. For instance, a large shipping company with thousands of customer cases can now categorize and access necessary information far more efficiently.” Additional Announcements Salesforce also introduced several new AI and Data Cloud features: Auradkar noted that these innovations enhance Salesforce’s competitive edge by prioritizing flexibility and enabling customers to take control of their data. “We’ll continue on this journey,” Auradkar said. “Our future investments will focus on how this product evolves and scales. We’re building significant flexibility for our customers to use any model they choose, including any large language model.” For more insights and updates, visit Salesforce’s official announcements and stay tuned for further developments. 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

June 9, 2024in Einstein 1 Platform, Hyperforce, Salesforce, Salesforce Einstein

07Jun

Data Cloud Vector Database and Hyperforce

Salesforce World Tour Highlights: Data Cloud Vector Database and Hyperforce At the Salesforce World Tour on June 6, 2024, at the Excel Centre in east London, the focus was on advancements in the Data Cloud and Slack platforms. The event, sponsored by AWS, Cognizant, Deloitte, and PWC, showcased significant innovations, particularly for GenAI enthusiasts. Data Cloud Vector Database and Hyperforce. Vector Database in Data Cloud A key highlight was the announcement of the general availability of a Vector Database capability within the Data Cloud, integrated into the Einstein 1 Platform. This capability enhances Salesforce’s CRM platform, Customer 360, by combining structured and unstructured data about end-users. The Vector Database collects, ingests, and unifies data, allowing enterprises to deploy GenAI across all applications without needing to fine-tune an off-the-shelf large language model (LLM). Addressing Data Fragmentation Salesforce reports that approximately 80% of customer data is dispersed across various corporate departments in an unstructured format, trapped in PDFs, emails, chat conversations, and transcripts. The Vector Database unifies this fragmented data, creating a comprehensive profile of the customer journey. This unified approach not only improves customer engagement but also enhances organizational agility. By consolidating data from all corporate silos, companies can quickly and efficiently address issues such as product recalls and returns. Hyperforce: Enhancing Data Residency and Compliance During the keynote, Salesforce emphasized the importance of personalization in customer engagement and the benefits of deploying GenAI in customer-facing sectors. The event highlighted the need to overcome the fear and mistrust of GenAI and showcased how enterprises can enhance employee productivity through upskilling in GenAI technologies. One notable announcement was the general availability of Hyperforce, a solution designed to address data residency issues by integrating all Salesforce applications under the same compliance, security, privacy, and scalability standards. Built for the public cloud and composed of code rather than hardware, Hyperforce ensures safe delivery of applications worldwide, offering a common layer for deploying all application stacks and handling data compliance in a fragmented technology landscape. Salesforce AI Center The Salesforce AI Center was also introduced at the event. The first of its kind, located in the Blue Fin Building near Blackfriars, London, this center will support AI experts, Salesforce partners, and customers, facilitating training and upskilling programs. Set to open on June 18, 2024, the center aims to upskill 100,000 developers worldwide and is part of Salesforce’s $4 billion investment in the UK and Ireland. Industry Reactions and Future Prospects GlobalData senior analyst Beatriz Valle commented on Salesforce’s continued integration of GenAI across its portfolio, including platforms like Tableau, Einstein for analytics, and Slack for collaboration. According to Salesforce, the Data Cloud tool leverages all metadata in the Einstein 1 Platform, connecting unstructured and structured data, reducing the need for fine-tuning LLMs, and enhancing the accuracy of results delivered by Einstein Copilot, Salesforce’s conversational AI assistant. Vector databases, while not new, have gained prominence due to the GenAI revolution. They power the retrieval-augmented generation (RAG) technique, linking proprietary data with large language models like OpenAI’s GPT-4, enabling enterprises to generate more accurate results. Competitors such as Oracle, Amazon, Microsoft, and Google also offer vector databases, but Salesforce’s early investments in GenAI are proving fruitful with the launch of the Data Cloud Vector Database. Data Cloud Vector Database and Hyperforce Salesforce’s AI-powered integration solutions, highlighted during the World Tour, underscore the company’s commitment to advancing digital transformation. By leveraging GenAI and innovative tools like the Vector Database and Hyperforce, Salesforce is enabling enterprises to overcome the challenges of data fragmentation and compliance, paving the way for a more agile and competitive digital future. 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

June 7, 2024in Einstein 1 Platform, Hyperforce, Salesforce, Salesforce Data Cloud

30Dec

January ’24 Einstein Data Cloud Updates

Utilize Generative AI to Target Audiences Effectively Harness the power of generative AI with Einstein Segment Creation in Data Cloud to create precise audience segments. Describe your target audience, and Einstein Segment Creation swiftly produces a segment using trusted customer data available in Data Cloud. This segment can be easily edited and fine-tuned as necessary. Jan ’24 Einstein Data Cloud Updates. Where: This enhancement is applicable to Data Cloud in Developer, Enterprise, Performance, and Unlimited editions. Einstein generative AI is accessible in Lightning Experience. When: This functionality is rolling out gradually, starting in Spring ’24. How: In Data Cloud, create a new segment and choose Einstein Segment Creation. In the Einstein panel, input a description of your segment using simple text, review the draft, and make adjustments as needed. Gain Insights into Segment Performance with Segment Intelligence Analyze segment data efficiently with Segment Intelligence, an in-platform intelligence tool for Data Cloud for Marketing. Offering a straightforward setup process, out-of-the-box data connectors, and pre-built visualizations, Segment Intelligence aids in optimizing segments and activations across various channels, including Marketing Cloud Engagement, Google Ads, Meta Ads, and Commerce Cloud. Where: This update applies to Data Cloud in Developer, Enterprise, Performance, and Unlimited editions. Utilizing Segment Intelligence requires a Data Cloud Starter license. When: For details regarding timing and eligibility, contact your Salesforce account executive. How: To configure Segment Intelligence, navigate to Salesforce Setup. To view Segment Intelligence dashboards, go to Data Cloud and select the Segment Intelligence tab. Activate Audiences on Google DV360 and LinkedIn Effortlessly activate audiences on Google DV360 and LinkedIn as native activation destinations in Data Cloud. Directly use segments for targeted advertising campaigns and insights reporting. Where: This change is applicable to Data Cloud in Developer, Enterprise, Performance, and Unlimited editions. Requires an Ad Audiences license. When: This functionality is available starting in March 2024. Enhance Identity Resolution with More Frequent Ruleset Processing Experience more timely ruleset processing as rulesets now run automatically whenever your data changes. This improvement eliminates the need to wait for a daily ruleset run, ensuring efficient and cost-effective processing. Where: This update applies to Data Cloud in Developer, Enterprise, Performance, and Unlimited editions. Refine Identity Resolution Match Rules with Fuzzy Matching Extend the use of fuzzy matching to more fields, allowing fuzzy matching on any text field in your identity resolution match rules. Up to two fuzzy match fields, other than first name, can be used in a match rule, with a total of six fuzzy match fields in any ruleset. Enhance match rules by updating to the “Fuzzy Precision – High” method for fields like last name, city, and account. Where: This enhancement applies to Data Cloud in Developer, Enterprise, Performance, and Unlimited editions. Salesforce Einstein’s AI Capabilities Salesforce Einstein stands out as a comprehensive AI solution for CRM. Notable features include being data-ready, eliminating the need for data preparation or model management. Simply input data into Salesforce, and Einstein seamlessly operates. Additionally, Salesforce introduces the Data Cloud, formerly known as Genie, as a significant AI-powered product. This platform, combining Data Cloud and AI in Einstein 1, empowers users to manage unstructured data efficiently. The introduction of the Data Cloud Vector Database allows for the storage and retrieval of unstructured data, enabling Einstein Copilot to search and interpret vast amounts of information. Salesforce also unveils Einstein Copilot Search, currently in closed beta, enhancing AI search capabilities to respond to complex queries from users. Jan ’24 Einstein Data Cloud Updates This groundbreaking offering addresses the challenge of managing unstructured data, a substantial portion of business data, and complements it with the capability to use familiar automation tools such as Flow and Apex to monitor and trigger workflows based on changes in this data. Overall, Salesforce aims to revolutionize how organizations handle unstructured data with these innovative additions to the Data Cloud. Like2 Related Posts Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more

December 30, 2023in Einstein 1 Platform, Einstein Insights, Salesforce Data Cloud, Salesforce Einstein

14Dec

Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities

Salesforce (NYSE: CRM) has announced major updates to its Einstein 1 Platform, introducing the Data Cloud Vector Database and Einstein Copilot Search. These new features aim to power AI, analytics, and automation by integrating business data with large language models (LLMs) across the Einstein 1 Platform. Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities. Unifying Business Data for Enhanced AI The Data Cloud Vector Database will unify all business data, including unstructured data like PDFs, emails, and transcripts, with CRM data. This will enable accurate and relevant AI prompts and Einstein Copilot, eliminating the need for expensive and complex fine-tuning of LLMs. Built into the Einstein 1 Platform, the Data Cloud Vector Database allows all business applications to harness unstructured data through workflows, analytics, and automation. This enhances decision-making and customer insights across Salesforce CRM applications. Introducing Einstein Copilot Search Einstein Copilot Search will provide advanced AI search capabilities, delivering precise answers from the Data Cloud in a conversational AI experience. This feature aims to boost productivity for all business users by interpreting and responding to complex queries with real-time data from various sources. Key Features and Benefits Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities Data Cloud Vector Database Einstein Copilot Search Addressing the Data Challenge With 90% of enterprise data existing in unstructured formats, accessing and leveraging this data for business applications and AI models has been challenging. As Forrester predicts, the volume of unstructured data managed by enterprises will double by 2024. Salesforce’s new capabilities address this by enabling businesses to effectively harness their data, driving AI innovation and improved customer experiences. Salesforce’s Vision Rahul Auradkar, EVP and GM of Unified Data Services & Einstein, stated, “The Data Cloud Vector Database transforms all business data into valuable insights. This advancement, coupled with the power of LLMs, fosters a data-driven ecosystem where AI, CRM, automation, Einstein Copilot, and analytics turn data into actionable intelligence and drive innovation.” Practical Applications Customer Success Story Shohreh Abedi, EVP at AAA – The Auto Club Group, highlighted the impact: “With Salesforce automation and AI, we’ve reduced response time for roadside events by 10% and manual service cases by 30%. Salesforce AI helps us deliver faster support and increased productivity.” Availability Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities Salesforce’s new Data Cloud Vector Database and Einstein Copilot Search promise to revolutionize how businesses utilize their data, driving AI-powered innovation and improved customer experiences. Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities 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

December 14, 2023in Einstein 1 Platform, Salesforce

22Nov

Salesforce Einstein 1 Platform

Salesforce unveils the groundbreaking Einstein 1 Platform, a transformative force in enterprise AI designed to enhance productivity and cultivate trusted customer experiences by seamlessly integrating data, AI, and CRM. This advanced platform meets the demands of a new AI era, adeptly managing extensive disconnected data, offering flexibility in AI model selection, and seamlessly integrating with workflow processes while prioritizing customer trust. Salesforce Einstein 1 Platform is a game changer from Salesforce. What is the Salesforce Einstein 1 platform? Einstein 1 has a mixture of artificial intelligence tools on the platform, and it kind of mirrors the way the core Salesforce platform is built, standardized and custom. We have out of the box AI features such as sales email generation in Sales Cloud, and service replies in Service Cloud. The Einstein 1 Platform consolidates data, AI, CRM, development, and security into a unified, comprehensive platform, empowering IT professionals, administrators, and developers with an extensible AI platform for rapid app development and automation. Streamlining change and release management, the DevOps Center allows centralized oversight of project work at every stage of the application lifecycle management process, ensuring secure data testing and AI app deployment. Salesforce customizes security and privacy add-on solutions, including data monitoring and masking, backup implementation, and compliance with evolving privacy and encryption regulations. Grounded in the Einstein 1 Platform, Salesforce AI delivers trusted and customizable experiences by leveraging customer data to create predictive and generative interactions tailored to diverse business needs. What are the Einstein platform products? Commerce Cloud Einstein is a generative AI tool that can be used to provide personalized commerce experiences throughout the entire buyer’s journey. It can be used to generate auto-generated recommendations, content, and communications that are based on real-time data from the Data Cloud. Einstein 1 serves as a comprehensive solution for organizations seeking a unified 360-degree view of their customers, integrating Silverline expertise to maximize AI potential and scalability. The introduction of Einstein 1 Data Cloud addresses data integration challenges, enabling users to connect any data source for a unified customer profile enriched with AI, automation, and analytics. Salesforce Data Cloud unifies and harmonizes customer data, enterprise content, telemetry data, Slack conversations, and other structured and unstructured data to create a single view of the customer. Einstein 1 Data Cloud is natively integrated with the Einstein 1 Platform and allows companies to unlock siloed data and scale in entirely new ways, including: Supporting thousands of metadata-enabled objects per customer, the platform ensures scalability, while re-engineering Marketing Cloud and Commerce Cloud onto the Einstein 1 Platform enables seamless incorporation of massive data volumes. Salesforce offers Data Cloud at no cost for Enterprise Edition or above customers, underscoring its commitment to supporting businesses at various stages of maturity. Einstein Copilot Search and the Data Cloud Vector Database further enhance Einstein 1 capabilities, providing improved AI search and unifying structured and unstructured data for informed workflows and automation. Einstein 1 introduces generative AI-powered conversational assistants, operating within the secure Einstein Trust Layer to enhance productivity while ensuring data privacy. Businesses are encouraged to embrace Einstein 1 as a strategic move toward becoming AI-centric, leveraging its unified data approach to effectively train AI models for informed decision-making. Salesforce’s Einstein 1 Platform introduces the Data Cloud Vector Database, seamlessly unifying structured and unstructured business data to enhance AI prompts and streamline workflows. Generative AI impacts businesses differently, augmenting processes to improve efficiency and productivity across sales, service, and field service teams. Einstein 1 Platform addresses challenges of fragmented customer data, offering a unified view for effective AI model training and decision-making. Salesforce’s continuous evolution ensures businesses have access to cutting-edge AI technologies, positioning Einstein 1 as a crucial tool for staying ahead in the AI-centric landscape. Ready to explore Data Cloud for Einstein 1? Limited access is available for $0, offering businesses an exclusive opportunity to leverage this transformative solution. Salesforce’s Einstein 1 Platform introduces advancements in AI search capabilities and unification of structured and unstructured business data, empowering informed workflows and automation. Einstein GPT expands conversational AI across Marketing and Commerce clouds, with the Data Cloud Vector Database playing a pivotal role in unifying data for Einstein 1 users. Einstein now has a generative AI-powered conversational AI assistant that includes Einstein Copilot and Einstein Copilot Studio. These two capabilities operate within the Einstein Trust Layer – a secure AI architecture built natively into the Einstein 1 Platform that allows you to leverage generative AI while preserving data privacy and security standards. Einstein Copilot is an out-of-the-box conversational AI assistant built into the user experience of every Salesforce application. Einstein Copilot drives productivity by assisting users within their flow of work, enabling them to ask questions in natural language and receive relevant and trustworthy answers grounded in secure proprietary company data from Data Cloud. Data Cloud Vector Database simplifies data integration, enhancing AI prompts without costly updates to specific business models. Data Cloud, integrated with the Einstein Trust Layer, provides secure data access and visualization, enabling businesses to fully harness generative AI. Einstein 1, with Data Cloud, offers a solution for organizations seeking comprehensive customer insights, guided by Silverline expertise for AI maximization. Salesforce’s Einstein 1 Platform securely integrates data, connecting various products to empower customer-centric businesses with AI-driven applications. Data Cloud for Einstein 1 supports AI assistants and enhances customer experiences, driving productivity and reducing operational costs. Einstein 1’s impact is evident in increased productivity and enhanced customer experiences, with ongoing evolution ensuring businesses stay at the forefront of AI technology. Generative AI augments existing processes, particularly in sales, service, and customer support, with Einstein 1 providing tools for streamlined operations. Salesforce’s Einstein 1 Platform introduces AI search enhancements and unified data capabilities, empowering businesses with informed decision-making and automation. Ready to embrace AI-driven productivity? Explore Data Cloud for Einstein 1 and revolutionize your business operations today. 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

November 22, 2023in Einstein 1 Platform, Salesforce, Salesforce Einstein

26Oct

RAG – Retrieval Augmented Generation in Artificial Intelligence

Salesforce has introduced advanced capabilities for unstructured data in Data Cloud and Einstein Copilot Search. By leveraging semantic search and prompts in Einstein Copilot, Large Language Models (LLMs) now generate more accurate, up-to-date, and transparent responses, ensuring the security of company data through the Einstein Trust Layer. Retrieval Augmented Generation in Artificial Intelligence has taken Salesforce’s Einstein and Data Cloud to new heights. These features are supported by the AI framework called Retrieval Augmented Generation (RAG), allowing companies to enhance trust and relevance in generative AI using both structured and unstructured proprietary data. RAG Defined: RAG assists companies in retrieving and utilizing their data, regardless of its location, to achieve superior AI outcomes. The RAG pattern coordinates queries and responses between a search engine and an LLM, specifically working on unstructured data such as emails, call transcripts, and knowledge articles. How RAG Works: Salesforce’s Implementation of RAG: RAG begins with Salesforce Data Cloud, expanding to support storage of unstructured data like PDFs and emails. A new unstructured data pipeline enables teams to select and utilize unstructured data across the Einstein 1 Platform. The Data Cloud Vector Database combines structured and unstructured data, facilitating efficient processing. RAG in Action with Einstein Copilot Search: RAG for Enterprise Use: RAG aids in processing internal documents securely. Its four-step process involves ingestion, natural language query, augmentation, and response generation. RAG prevents arbitrary answers, known as “hallucinations,” and ensures relevant, accurate responses. Applications of RAG: RAG offers a pragmatic and effective approach to using LLMs in the enterprise, combining internal or external knowledge bases to create a range of assistants that enhance employee and customer interactions. Retrieval-augmented generation (RAG) is an AI technique for improving the quality of LLM-generated responses by including trusted sources of knowledge, outside of the original training set, to improve the accuracy of the LLM’s output. Implementing RAG in an LLM-based question answering system has benefits: 1) assurance that an LLM has access to the most current, reliable facts, 2) reduce hallucinations rates, and 3) provide source attribution to increase user trust in the output. Retrieval Augmented Generation in Artificial Intelligence Content updated July 2024. Like2 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

October 26, 2023in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Data Cloud

27Jul

How Data Cloud Vector Databases Work

How Data Cloud Vector Databases Work 1. Ingest Unstructured Data in Data Cloud With the help of a new, unstructured data pipeline, relevant unstructured data for case deflection, such as product manuals or upgrade eligibility knowledge articles, can be ingested in Data Cloud and stored as unstructured data model objects. 2. Chunk and Transform Data for Use in AI In Data Cloud, teams will then be able to select the data that they want to use in processes like search, chunking this data into small segments before converting it into embeddings – numeric representations of data optimized for use in AI algorithms. This is done through the Einstein Trust Layer, which securely calls a special type of LLM called an “embedding model” to create the embeddings. It is then indexed for use in search across the Einstein 1 platform alongside structured data. How Data Cloud Vector Databases Work. 3. Store Embeddings in Data Cloud Vector Database In addition to supporting chunking and indexing of data, Data Cloud now natively supports storage of embeddings – a concept called “vector storage”. This frees up time for teams to innovate with AI instead of managing and securing an integration to an external vector database. 4. Analyze and Act on Unstructured Data Use familiar platform tools like Flow, Apex, and Tableau to use unstructured data, such as clustering customer feedback by semantic similarity and creating automations that alert teams when sentiment changes significantly. 5. Deploy AI Search in Einstein Copilot to Deflect Cases With relevant data, such as knowledge articles, securely embedded and stored in Data Cloud’s vector database, this data can also be activated for use in Einstein AI Search within Einstein Copilot. When a customer visits a self-service portal and asks for details on how to return a product, for example, the Einstein Copilot performs semantic search by converting the user query into an embedding, after which it compares that query to the embedded data in Data Cloud, retrieving the most semantically relevant information for use in its answer while citing the sources it pulled from. The end result is AI-powered search capable of understanding the intent behind a question and retrieving not just article links but exact passages that best answer the question, all of which are summarized through a customer’s preferred LLM into a concise, actionable answer – boosting customer satisfaction while deflecting cases. 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

July 27, 2023in Einstein 1 Platform, Salesforce Data Cloud

Data Cloud Vector Database and Hyperforce

January ’24 Einstein Data Cloud Updates

Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities

Salesforce Einstein 1 Platform

RAG – Retrieval Augmented Generation in Artificial Intelligence

How Data Cloud Vector Databases Work

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