New Vector Database in Salesforce Data Cloud Will Power AI, Analytics, and Automation Using LLMs with Business Data for Use Across the Einstein 1 Platform
14 Dezembro 2023 - 10:00AM
Business Wire
Data Cloud Vector Database will unify all
business data, including unstructured data like PDFs, emails, and
transcripts, with CRM data to enable grounding of AI prompts and
Einstein Copilot, eliminating the need for costly and complex
fine-tuning of LLM models
Data Cloud Vector Database will be built into
the Einstein 1 Platform, enabling all business applications to
harness the power of unstructured data through workflows,
analytics, and automation
Einstein Copilot Search will provide AI search
capabilities to deliver precise answers from Data Cloud instantly
in a conversational AI experience — boosting productivity for all
business users
Salesforce (NYSE: CRM) today announced significant updates to
its Einstein 1 Platform, adding the Data Cloud Vector Database and
Einstein Copilot Search.
This press release features multimedia. View
the full release here:
https://www.businesswire.com/news/home/20231214574921/en/
Einstein Copilot Search enables patterns
like Retrieval Augmented Generation to make AI more trusted and
relevant (Graphic: Business Wire)
Accurate and relevant generative AI prompts require grounding in
the most comprehensive set of enterprise data. Until now, this has
required expensive and labor-intensive model fine-tuning. Data
Cloud Vector Database will solve this challenge by making it
quick and easy to bring unified business data into any AI prompt so
customers can deploy trusted, relevant generative AI across all
Salesforce applications without having to fine-tune an
off-the-shelf large language model (LLM).
Data Cloud Vector Database – built into the Einstein 1 Platform
– enables AI, automation, and analytics for improved
decision-making and customer insights across all Salesforce CRM
applications. Data Cloud will also power Einstein Copilot
Search — announced today — enhancing Einstein Copilot,
Salesforce's generative AI assistant, with AI search capabilities
that use all business data to deliver more precise information,
conveniently in the flow of work.
New capabilities:
Data Cloud Vector Database
Data Cloud Vector Database will remove the
need to fine-tune LLMs by seamlessly using all business data to
enrich AI prompts, allowing customers to use a variety of data
types across their business applications and workflows. This
increases business value and ROI by unifying unstructured data,
including PDFs, emails, documents, and transcripts, with structured
data, including purchase history, customer support cases, and
product inventory, to power AI, automation, and analytics across
every Salesforce application.
For example, customer service leaders will
enhance efficiency and customer satisfaction by utilizing a
platform that proactively presents relevant knowledge articles to
service agents the moment a case is created. This allows for quick
identification of similar cases and the integration of automation,
thereby reducing case resolution time and improving the overall
customer experience.
Einstein Copilot Search
Einstein Copilot, available in February, will
include enhanced AI search capabilities that interpret and respond
to complex queries from users by tapping into diverse data sources,
including unstructured data. Einstein Copilot Search will enhance
Einstein Copilot, providing sales, customer service, marketing,
commerce, and IT teams with an AI assistant capable of solving
problems and generating content by accessing real-time unstructured
and structured business data. Customers will benefit from an AI
assistant that understands and addresses complex queries by
accessing insights and knowledge previously unattainable with
foundational LLMs due to limitations in their training data.
Einstein Copilot Search also provides citations to source material.
Salesforce's Einstein Trust Layer builds trust and confidence in
AI-generated content while maintaining data governance and
security.
For example, in customer service, Einstein
Copilot Search will link a customer's concerns from unstructured
emails and phone call transcripts to their structured support
ticket history. This provides service representatives with a
detailed understanding of customer issues and their historical
context and AI-generated, data-backed resolution suggestions. And,
the new integration of source citations enhance the customer
service team's confidence in the AI-generated insights.
Why it matters: Data is crucial for delivering accurate,
compelling customer experiences and driving AI innovation. However,
90% of enterprise data exists in unstructured formats like PDFs,
emails, social media posts, and audio files, making it largely
inaccessible for business applications and AI models. Forrester
predicts* that the volume of unstructured data managed by
enterprises will double by 2024, highlighting the urgency of this
challenge. While 80% of IT leaders acknowledge the transformative
potential of generative AI in leveraging data more effectively, 59%
still need a unified data strategy to harness this power.
Salesforce perspective:
- "The Data Cloud Vector Database relieves the challenge of
costly and complex processes to harness the value of unstructured
data. Now, our customers can reason over their full spectrum of
their enterprise data to power their business applications more
effectively. By integrating both structured and unstructured data,
our new Data Cloud Vector Database transforms all business data,
from emails to documents to transcripts to social media posts, into
valuable insights. This advancement in Data Cloud, coupled with the
power of LLMs, is a game-changer, fostering a data-driven ecosystem
where AI, CRM, automation, Einstein Copilot, and analytics turn
data into actionable intelligence and drive innovation." — Rahul
Auradkar, EVP and GM of Unified Data Services &
Einstein
Use cases:
- Customers can receive better, more automated customer
service. Customers visiting a self-service page can ask the
Einstein Copilot-powered chatbot about upgrade eligibility. The
chatbot answers by pulling relevant details from multiple knowledge
sources, and citing the specific source articles.
- Service leaders can improve productivity and customer
experiences by understanding service-related trends. To improve
customer experiences, call center leaders can use unstructured data
and AI to automatically compare cases and identify those that are
similar in their intent, triggering automated Flows that alert case
owners if a new case is a potential duplicate. Service leaders can
also use analytics tools like Tableau to cluster knowledge articles
and spot trends across newly created cases and articles, helping
uncover new ways to deliver better customer experiences.
- Marketers can tailor campaigns based on consumer intent and
behavior. When building a campaign, a marketer can use
Marketing Cloud Intelligence to understand consumer intent by
analyzing unstructured survey data and transcripts in Data Cloud,
then iterate on email templates and copy them directly from within
Einstein Copilot through natural language instructions.
- Commerce teams can generate new product descriptions
faster. When creating a product description, a brand manager
can ask Einstein Copilot to compare the details of a new product
against existing products that are similar. They can use the
information contained in product catalogs from closely related
products to generate relevant descriptions quickly.
- Sales can increase revenue using AI to surface insights from
prior customer interactions. To prepare for a customer meeting,
a sales rep can have Einstein Copilot reference specific
unstructured data, like a customer’s 10-K or past email
interactions, and ask questions about that data. Responses will
include relevant information such as the top three initiatives for
the customer’s company in the next fiscal year and who the new
executive bench includes, setting the sales rep up with valuable
insights for their meeting.
- IT can discover problems and anomalies in product
telemetry. Unstructured content produced from machine
operations, including machine logs, sensor readings, images, or
audio recordings, can be ingested into Data Cloud. Tableau can then
analyze this data and Einstein can identify and flag unusual data
points through semantic similarity that reveal problems with the
equipment.
Customer perspective:
- “With Salesforce automation and AI technology, we have reduced
response time for our 6 million annual roadside events by 10%. Our
reps have access to real-time data, helping them quote field
service arrival times more accurately, automate fleet deployment,
and personalize service to members in crisis. Additionally, members
can use self-service options from anywhere, which has reduced
manual service cases by 30%. As we plan for the road ahead,
Salesforce AI will help us serve members more efficiently across
the company, including our insurance business, by distilling
complex insurance policies into swift, customer-centric responses,
delivering faster support for clients and increased productivity
for agents." — Shohreh Abedi, EVP, Chief Operations
Technology Officer, and Member Experience at AAA – The Auto Club
Group
Availability:
- Data Cloud Vector Database will be in pilot in February
2024
- Einstein Copilot Search will be in pilot in February 2024
- Einstein Copilot will be generally available in February
2024
Learn More:
- Learn more about the Einstein 1 Platform
- Learn about Salesforce Data Cloud, which now processes over 100
billion customer records daily
- Dive deeper into retrieval augmented generation (RAG)
- Watch World Tour NYC live for more on Salesforce’s latest
innovations
*Forrester, Predictions 2024: Data and Analytics by Zeid Khater,
26 October 2023
Any unreleased services or features referenced here are not
currently available and may not be delivered on time or at all.
Customers should make their purchase decisions based upon features
that are currently available.
View source
version on businesswire.com: https://www.businesswire.com/news/home/20231214574921/en/
Steve Mnich Smnich@salesforce.com
Salesforce (NYSE:CRM)
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