Customer Service Automation · Enterprise Knowledge Search
Datasite needed faster, more accurate support for dealmakers running high-stakes M&A transactions, but its first-generation Einstein chatbot could not transfer chats to humans or keep answers current without manual updates.
Reported impact
Datasite improved self-service quality for time-sensitive deal support, expects a higher automated resolution rate than its earlier chatbot, and frees the Assist team to spend more time on consultative, high-touch work.
Datasite evolved its support architecture from a basic Einstein chatbot into a more dynamic Agentforce workflow that lives in Experience Cloud and draws on both operational and knowledge data. The earlier Einstein implementation already used a knowledge base with more than 2,000 articles to resolve common questions, but the handoff to live support and freshness of answers remained a bottleneck for urgent deal workflows. Agentforce now verifies the user's identity and permissions, retrieves the most relevant knowledge for a natural-language question, automatically stays current with new product content, and passes the entire conversation plus account context to a human Assist team member when escalation is needed. Datasite also plans to extend the design by unifying structured knowledge in Snowflake with unstructured chats and emails in Salesforce through Data Cloud so the same agent layer can answer more nuanced product and case-history questions over time.
Customers start a chat in Experience Cloud, where Agentforce verifies identity, retrieves the best answer from Datasite knowledge content, and either resolves the issue or hands the interaction to the Assist team with a generated summary; over time, structured Snowflake content and Salesforce interactions are meant to converge in Data Cloud for richer answers.
Data Cloud will unify and harmonize this data and make it usable across Datasite's entire tech stack.
Datasite expects to use Agentforce to resolve 70% of incoming chat queries - 20% more than their Einstein chatbot.
Einstein ... tapped into Datasite's knowledge base of over 2,000 articles.
If a customer needs an Assist team member, Agentforce seamlessly transfers the case with a summary of the chat and key account details.
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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