openpitch 0.1.0

Open, real-time, fully-sourced intelligence on top AI startups — MCP-native, zero-cost.

🪧 OpenPitch

The open, real-time intelligence layer for AI startups — that any agent can build on.

A free, open-source alternative to PitchBook & CB Insights, focused on the AI companies VCs actually care about.

MCP-native · zero-cost · fully-sourced · updated daily

Status: v0.1.0 — functional. The pipeline, reconciliation engine, MCP server, and dashboard all work end-to-end (BRD · FRD · PRD). Coverage and source breadth keep growing via the daily run.

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Why OpenPitch exists

PitchBook and CB Insights cost $20k+/year — and for fast-moving AI startups, their data is often months stale, because human verification is slow. For a company growing 3× a year, a figure verified six months ago can be off by multiples.

Meanwhile, the real numbers are already public: founders state ARR on podcasts weeks before any database, funding hits SEC filings, hiring velocity reveals growth. They're just scattered, unstructured, and contradictory — exactly the problem an AI agent is built to solve.

OpenPitch's bet is latency, not coverage. For ~50 top AI companies, a fresh, fully-sourced, confidence-scored number beats a verified-but-stale one. We don't claim certainty — we show you the receipts.

What you get

Ask your coding agent, get an answer with receipts:

> what's Mistral's latest ARR and who led their last round?

  Mistral AI
  ARR        ~€30M (implied, medium confidence) · as of 2026-05
  Last round $640M Series B · led by General Catalyst
  ↳ source: founder on 20VC ep.1042 · SEC filing · The Information
  ↳ ARR moved €18M → €30M (+67%) since 2026-01

Every number carries its source, a confidence score, and a tracked history of how it changed.

Features

• 🎙️ Mines podcasts — founders leak metrics on podcasts before any database catches them. We transcribe and extract them.
• 🧾 Always sourced — every figure links to its origin (podcast timestamp, filing, article). No black-box numbers.
• 📊 Confidence-scored — built from source reliability, speaker authority, corroboration, and freshness (confidence decays as data ages).
• 🔀 Reconciles conflicts — when sources disagree, you get a consensus range + a contradiction flag, not a silent guess.
• 🧠 Learns which sources to trust — sources that prove right over time earn more weight.
• 🕒 Version-tracked — the git history is the audit log. See exactly how a company's reported ARR evolved.
• 📡 Composable — emits typed events other agents subscribe to (newsletters, press alerts, investor outbound).
• 🤝 Agent-to-agent (A2A) — not just an MCP tool but an A2A agent your agents can delegate research to.
• 🧯 Grounding — give your AI a sourced, confidence-scored fact base so it stops making up AI-company numbers.
• ⚡ 60-second install — no key, no signup; works in your agent in under a minute.
• 💸 Genuinely free — runs entirely on free tiers. No cost to run, no cost to use.

Quickstart — use it in Claude Code / Codex

No API key. No signup. No cost. The data is already built and committed; the MCP server just reads it, and your agent does the reasoning.

Fastest — zero install (reads the committed data from the public repo, no clone):

uvx openpitch-mcp

Or install the package:

pip install openpitch          # the MCP server (mcp is a core dependency)
openpitch-mcp                  # start the read-only server

Or run from a clone (for the pipeline / to rebuild data):

git clone https://github.com/Avierovich/openpitch && cd openpitch
python -m venv .venv && source .venv/bin/activate
pip install -e ".[pipeline]"   # core + pipeline LLM deps
openpitch seed                 # build the data/ database from the committed seed (offline, no key)

Then point your agent at the local server:

// MCP config (Claude Code / Codex). Published path will be: {"command":"uvx","args":["openpitch-mcp"]}
{
  "mcpServers": {
    "openpitch": { "command": "openpitch-mcp" }
  }
}

Ask your agent: "What's Cognition's ARR, with sources and confidence?" — it calls get_metric/get_provenance and answers from committed data (and will flag the public-source discrepancy).

Or just browse the data

• 🌐 Dashboard — openpitch build-dashboard → open dashboard/dist/index.html (sourced company cards; GitHub Pages at release)
• 📁 Raw data — data/companies/ — plain JSON, diffable, yours to use
• 🤝 A2A Agent Card — generated at dashboard/dist/.well-known/agent.json

Data status: the committed seed is verified enough for software testing but not launch-grade (see LAUNCH-GATES). The software is runnable end-to-end; the remaining launch risk is data quality, contradiction strength, and public demo polish.

Product docs

• Build scope — PRD, v0 seed dataset, launch gates
• Trust model — methodology, data policy, corrections
• Interfaces — MCP spec, events spec, FRD
• Go-to-market — competitive analysis, strategy deep dive
• Operations + brand — operations, recent changes, logo options

How it works

  Sources              Daily pipeline (free GitHub Actions)         Interfaces
  ──────────           ───────────────────────────────────         ──────────
  Podcasts ─┐          1. select top-50 (VC-attention score)        ┌─ MCP server (local, BYO agent)
  News ─────┤    ───▶  2. collect · 3. transcribe · 4. extract ───▶ ├─ static dashboard
  SEC EDGAR ┤          5. reconcile · 6. score sources              ├─ event feed (JSONL / RSS)
  Web ──────┘          7. publish → git commit (the database)       └─ "what moved today" digest

The git repo is the database. There's no server to run. See the FRD for the full design.

Build on it (composability)

OpenPitch emits typed, confidence-scored events when something material changes — so other agents can react:

You're building…	Subscribe to	OpenPitch becomes…
A newsletter agent	all material events	your content pipeline's data source
A press/PR workflow	funding/valuation events, confidence ≥ 0.8	your "time to call the company" trigger
Investor outbound	universe entries, growth thresholds	your targeting signal

Events ship on MCP and a raw events/feed.jsonl. Schemas are versioned. See the events spec.

How we compare

OpenPitch is complementary to the incumbents, not a rip-and-replace. We win a narrow wedge; we lose on breadth and verification — and we're honest about both.

	PitchBook / CB Insights	Crunchbase	Harmonic	MAGNiTT / Wamda	OpenPitch
Price	$20k–100k/yr	Freemium	Custom	$/regional	Free & open
Freshness	Weeks–months	Variable	Days	Weeks	Daily
In your AI agent (MCP)	✗	✗	◐	✗	✓
Every figure sourced + confidence-scored	◐	◐	◐	◐	✓
Contradiction detection	✗	✗	✗	✗	✓
Coverage breadth	✓✓✓	✓✓✓	✓✓	✓ (MENA)	narrow (by design)
Verified, diligence-grade	✓	◐	◐	◐	✗ (probabilistic)

The honest pitch: the free, fresh, AI-native first look — every number sourced — before you pull the expensive verified report. For an investment decision, you still need the incumbents. Full mapping, feature matrix & pricing: docs/COMPETITIVE-ANALYSIS.md · spreadsheet.

Coverage

Global AI startups — ~50, dynamically selected by VC attention (valuation + funding activity + investor quality — not ARR, to avoid circularity). The list moves as attention shifts; companies entering/leaving the top-50 is itself a tracked signal.

MENA AI/tech segment — a dedicated regional set (an open, AI-native alternative to MAGNiTT/Wamda). Honest caveat: MENA disclosure is lighter than the US, so this segment launches with lower confidence/coverage, clearly labeled.

Seed universe: config/watchlist.yaml.

Honest disclaimer

OpenPitch is transparently probabilistic. Many figures are estimates derived from public, self-reported, sometimes-contradictory sources. We surface confidence and provenance precisely so you can judge for yourself. This is not investment advice, and figures are not guaranteed accurate. Always verify before acting.

Roadmap

• Business + technical specs (BRD · FRD)
• Competitive analysis: incumbents · matrix xlsx · OSS landscape · free/open deep-dive · strategy & viability
• Seed universe (global AI + MENA segment)
• Core data model + reconciliation engine (confidence, consensus, contradiction) — tested
• Source adapters: podcast, news, EDGAR, company-site — tested
• Extraction stage: batched LLM claim extraction + model rotation — tested; data QA still required
• MCP server — local read-only data tools
• Daily GitHub Actions pipeline — wired for LLM, Groq transcription, and SEC user-agent secrets
• Static dashboard + company pages — generated from committed data
• Event feed — JSONL feed and digest generated from publishes
• A2A agent discovery card — generated with dashboard
• Brand direction — selected logo option 5, Terminal Proof
• MENA adapters (regional news, free-zone registries)
• Rich-source expansion (GitHub, hiring, app-ranks) — post-PMF scaling
• v2: implied-ARR model, intra-day funding fast-lane

Contributing

Contributions welcome — especially new source adapters (one file each) and watchlist curation. See the FRD for architecture.

License

MIT

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_{Built in the open. Free forever. If a number looks wrong, open an issue — provenance means you can check our work.}