Model ML Integrates with Snowflake

Model ML today announced an integration with Snowflake, connecting the platform where a firm's most valuable internal data lives to the place where the work gets done.

For most firms, Snowflake is the home of their proprietary data, including portfolio company KPIs, positions and exposures, CRM records, and fund performance. Users can now query that data directly inside Model ML, alongside filings, transcripts, and deal documents, across all their workflows, skills, and surfaces.

The connection uses Snowflake's own managed MCP server, which means nothing changes on the security side: permissions, access rules, and data governance carry over exactly as they are. Internal data becomes available to existing workflows without a new security model to review or maintain.

If your firm runs on Snowflake, you can connect it to Model ML today.

Snowflake in Model ML: Use Cases by Sector

• Private Equity: Query portfolio company KPIs and fund performance next to board decks, IC memos, and diligence materials, and connect CRM records with filings and transcripts to spot opportunities earlier.

• Investment Banking: Draft pitchbooks, comps, and IC materials that draw on CRM pipelines, positions, and the firm's own deal history alongside live market data.

• Consultancies: Build proposals and deliverables on client data and internal benchmarks from Snowflake, combined with filings, transcripts, and market research.