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GPTfy - Salesforce Native AI Platform

Snowflake as RAG. Cases Resolved Instantly.

GPTfy routes Salesforce case questions through Snowflake Cortex to find the exact document answer — then delivers it inside the case record, no additional license required.

Support reps no longer manually search technical documentation to answer case questions. GPTfy sends the case description to Snowflake Cortex, retrieves the relevant document, and surfaces an accurate, document-grounded AI answer directly inside the Salesforce case record.

What this demo covers

Snowflake Cortex Retrieval

  • Case description is extracted and sent to Snowflake Cortex for semantic document search.
  • Cortex identifies the most relevant document from your Snowflake knowledge store automatically.

Document-Grounded AI Answers

  • The retrieved document is attached to the AI prompt before processing — not general knowledge.
  • Answers reference your actual product specifications, runbooks, or policy documents directly.

Salesforce-Native Workflow

  • The entire RAG retrieval and AI generation cycle happens inside the Salesforce case record.
  • Support reps receive the answer in a readable format without leaving Salesforce.

No Additional License

  • No additional platform license is required to connect Snowflake as a RAG source.
  • GPTfy connects via standard API credentials through its API Data Source configuration.

Use this video when

A support rep receives a product specification question and needs the exact answer from a technical manual stored in Snowflake

A service team stores owner manuals, runbooks, and policy documents in Snowflake and wants them accessible from Salesforce cases

A support manager wants to standardize case resolution by grounding AI answers in official documentation rather than general AI knowledge

A Salesforce admin wants to enable RAG-powered case resolution without migrating documents into Salesforce Knowledge

A compliance-sensitive organization needs AI answers that cite specific internal documents rather than making inferences

An engineering team wants to reuse their existing Snowflake document store as a knowledge source for Salesforce support workflows

Frequently asked questions

When a support rep runs a GPTfy prompt on a Salesforce case, the API Data Source component extracts the case description and sends it to Snowflake Cortex. Cortex identifies the most relevant document from your knowledge store, returns that document to GPTfy, which then attaches it to the AI prompt for processing and delivers the answer inside the Salesforce case record.

The demo shows product owner manuals stored as documents in Snowflake. Any structured or semi-structured knowledge content can be stored and indexed — technical specifications, support runbooks, product guides, compliance documents, and policy materials. Snowflake Cortex handles the semantic search and retrieval.

Salesforce Knowledge Articles live inside Salesforce and require manual curation within the platform. Snowflake RAG allows you to store your knowledge in Snowflake — where you may already maintain technical documentation — and retrieve it semantically without migrating content into Salesforce. Both approaches can be used together through GPTfy.

No. As shown in the demo, this entire workflow — from case question to Snowflake Cortex retrieval to AI-generated answer inside Salesforce — operates without any additional platform license. GPTfy connects to Snowflake via its API Data Source feature using standard credentials.

Because the answer is grounded in the actual retrieved document rather than generated from general AI knowledge, responses are highly specific to your product or service. In the demo, the AI correctly cites the exact towing capacity specification from the owner manual stored in Snowflake, not a generalized estimate.

Yes. The RAG pattern works across any Salesforce object. A sales rep could retrieve product specifications, pricing guidelines, or competitive briefs stored in Snowflake directly from an opportunity record. The prompt and data source configuration determines which documents are retrieved for which workflows.

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Video transcript
In this demo, we are going to showcase GPTfy's capability that enables the end user to use their Snowflake database as a RAG, and use AI to generate insights or solve support cases right within Salesforce. For example, imagine a car company like Tesla using GPTfy with Salesforce. Meet Jacob. He is a support representative at Tesla. We are going to navigate his Salesforce and use GPTfy to show how a support representative could use it to quickly resolve a customer question. What you see on the screen is a prompt that GPTfy has configured for Jacob, which is basically a set of instructions for AI to follow as it generates a response. This is a Snowflake database where Jacob has the owner manual for a Cybertruck and the owner manual for Model Y stored. Moving back to Jacob's Salesforce. Jacob has a case over here with a question asked by a customer: "What's the towing capacity of Cybertruck?" Before he runs the prompt, let's see what is actually happening when Jacob runs the prompt. The API Data Source is going to retrieve the field description from this particular case and send the content to Cortex inside Snowflake. Cortex will identify the specific document where the question can be answered and send that back to Salesforce, where GPTfy will attach the resolution file to the prompt and send to AI for further processing and bring the response back within Jacob's Salesforce. Another amazing part of this whole process is that Jacob does not need any additional platform license for this to work. Let's run this prompt now. GPTfy has given us the answer inside Jacob's Salesforce, using Jacob's Snowflake as RAG. We can clearly see that the maximum towing capacity is up to 14,000 pounds over here, depending on the configuration — and payload capacity is designed to carry heavy loads in the bed. This response is from the knowledge base that was stored inside Jacob's Snowflake, made available to him in a readable format right inside his Salesforce.

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Last updated: February 2026