Salesforce Data Cloud updates aim to ease data analysis, AI app development
Salesforce has also added an AI search capability to Einstein Copilot, which will allow the generative AI-based assistant to interpret and respond to complex queries from enterprise users by tapping into diverse data sources, including unstructured data.
“Copilot Search will provide precise, contextually relevant responses in a user’s workflow and bolster trust with source citations from the Einstein Trust Layer,” the company said.
The Einstein Trust Layer is based on a large language model (LLM) built into the platform to ensure data security and privacy.
In order to take advantage of unstructured data via Einstein Copilot Search, enterprises would have to create a new data pipeline that can be ingested by the Data Cloud and stored as unstructured data model objects.
These data model objects have to be transformed into data fit for use in AI applications by converting the data into embeddings, which are numeric representations of data optimized for use in AI algorithms, the company said, adding that these embeddings are then indexed for use in search across the Einstein 1 platform alongside any other existing structured data.
The Einstein Copilot Search capability can also be paired with retrieval augmented generation (RAG) tools — which Salesforce supplies — in order to enable Einstein Copilot to answer customer questions. Answers comes with semantically relevant information, citing the knowledge sources used to craft the answers, the company said.
