PE firms run on precision: waterfalls, carry, capital accounts, and marks that must tie out. Generic AI tools can't help with any of it, because they can't see the data — and even if they could, fragmented systems mean there's no single version of the truth to query. Foresight solves the data problem first (unification, reconciliation, QA across fund accounting, cap tables, deal documents, and KPIs), then exposes it to AI through MCP.
"What's net IRR for Fund III at the LP level?" "Which positions have marks unsupported by a recent round?"
"Rank portfolio companies by EBITDA growth this year." "Which companies missed their quarterly submission?"
"Show our full financing and ownership history in [company]." "Model proceeds across the waterfall at a 3x exit."
"Draft the track-record section of the DDQ." "Summarize Fund II performance for the annual meeting."
Ask questions in Claude, ChatGPT, or Glean via the MCP server; in Foresight's own AI on desktop and mobile; in Excel through the plug-in; or build directly on unlimited API access and a hosted Snowflake warehouse. One reconciled data layer serves them all.
Answers trace to source documents and reconciled records, so a number quoted in an AI chat is the same number in the audit file. Foresight's AI runs on AWS Bedrock, whose no-training policy means model providers like Anthropic and OpenAI cannot use your data to train or improve their models. Foresight is SOC 2 and ISO 27001 certified and CCPA compliant, with encryption in transit and at rest and your firm's permissions enforced. In private markets, one number can have five sources — Foresight makes sure your AI only sees the right one.
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