From founder emails to LP reports automatically. Every quarter you spend 20 hours building LP reports by copying metrics from PowerPoint slides and Excel files that founders send you. Your LPs expect institutional-grade reporting but you're doing data entry by hand. I built a system that processes investor updates automatically — forward emails in any format, AI extracts the metrics, and you get real-time portfolio dashboards plus formatted reports ready for your next LP meeting.
Forward investor updates in any format — PDF, Excel, PowerPoint, plain text — and AI identifies the company, extracts metrics, and builds portfolio dashboards. Track and report investment performance metrics at company, fund, and portfolio levels. Generate institutional-grade LP reports without manual data entry.
- Email forwarding — Give founders an inbound address, system processes everything automatically
- AI extraction — Identifies companies and pulls metrics like MRR, burn rate, headcount, and any custom KPIs you set from any format
- Portfolio dashboard — Real-time view of company health with key metrics and trend analysis
- Review queue — Flags uncertain extractions for human verification before saving
- LP reporting — Export clean data or use built-in templates for professional presentation
- Lightweight CRM - Track intros, strategy, qualitative value-adds to demonstrate how you work with your portfolio
- Inbound deal screening — Cold pitches and partner-forwarded intros sent to your inbound address get classified, fit-scored against your thesis, and queued in a Deals pipeline. Optional public submission form for founders.
- Diligence — Pre-investment record-keeping with a schema-driven AI agent that ingests the data room, runs external research, asks partner Q&A, drafts a structured memo with paragraph-level provenance, and renders to Word or Google Docs. Schemas (rubric, Q&A library, memo structure) are partner-editable per fund.
Detailed feature descriptions at FEATURES
- Data consistency and availability - One source of truth for your team. Reduce your reliance on a maze of spreadsheets. Everyone works from the same portfolio data, metrics, and reports from a central location.
- Built to work with AI - Bring your fund data to your own AI, and use it to ask anything about your portfolio and fund. Ask about benchmarks, trends, industry data, research, and more.
- Professionalize internal operations - Institutional-quality reporting infrastructure without the cost of enterprise software. Run it yourself, on your own terms.
- Built for how funds work - Designed by a fund CFO for key workflows, including investor updates, LP reporting, and portfolio monitoring. Works alongside your fund admin and operations team.
I've spent over a decade as a fund CFO, investor, and consultant — working with thousands of GPs and founders on the exact problem this tool solves: manually collecting, analyzing, and presenting portfolio data every quarter.
Most portfolio reporting platforms lock your data in their database, process it through their AI, and charge per seat so half your team can't log in. Fund managers shouldn't have to choose between good tooling and owning their data.
This is a complete portfolio reporting platform you deploy on your own infrastructure — your database, your AI keys, your domain. It's open source under the Apache 2.0 license: free to use, modify, and run forever, for your own fund or commercially. No per-seat fees. No black-box AI training on your portfolio. No vendor lock-in.
Built by Taylor Davidson at Hemrock. Built by a fund manager, for fund managers.
Free and open source under the Apache 2.0 license — use it, modify it, and deploy it on your own infrastructure and domain, for your own fund or commercially. Try the demo with sample data, no signup required.
Prefer not to run it yourself? Taylor offers paid setup & support (deployed on your own infrastructure and accounts) and an early-access hosted subscription. Contact Taylor to discuss.
See LICENSE for full terms.
- Clone the repo — git clone https://github.com/tdavidson/reporting.git && npm install
- Create a Supabase project — Copy your project URL, anon key, and service role key
- Generate an encryption key — openssl rand -hex 32
- Deploy to Netlify or Vercel — One-click deploy buttons available in the full guide
- Configure auth and add your first user — Set Supabase redirect URLs and whitelist your email
- Add an AI key and forward your first email — Anthropic, OpenAI, Gemini, or run your LLM locally
Full deployment guide with detailed steps, optional services, and local development setup: DOCS
For setup assistance or hosted deployments: hemrock.com/contact. For bug reports and feature requests: GitHub Issues.