The whole stack, on your terms.
A sub-$50M fund runs everything a big fund runs, with a fraction of the team. This is the operating layer for all of it: monitoring, diligence, LP reporting, and real books, on infrastructure you own.
The problem you have
Small funds carry the same obligations as large ones. You screen deals, diligence the ones that advance, monitor the portfolio, and report to LPs on a schedule, all without the headcount to make any of it easy. The platforms built for institutional funds solve this, then charge per seat and keep your data in their database.
This runs the full stack and leaves it on your infrastructure. Deal flow gets screened and scored against your thesis. An AI agent reads the data room, runs outside research, and drafts a memo with provenance on every paragraph. The portfolio tracks itself from founder updates, LP letters draft from live data, and a double-entry ledger per vehicle produces the numbers when you want them from real books. Your database, your AI keys, no per-seat fee.
What matters most for a micro fund
Deal screening and diligence
Pitches get scored against your thesis, and an AI agent reads the data room, runs outside research, and drafts a structured memo you edit and sign off.
Portfolio monitoring
Founder updates become dashboards, with a review queue for anything the AI isn't sure about.
LP capital, portal, and accounting
Report to LPs from live data, give them a branded portal, and keep real books per vehicle with period close when you want them.
Every module is a switch that's off by default. Run the piece you need and ignore the rest. See everything it does.
Model what this doesn't
Reporting runs on live data. When you need to model forward, the Hemrock models pick up where the app stops.
