Fundraising intelligence that gets smarter with every raise.
See it work
We're building an AI code review platform. $1.8M ARR, 45% MoM growth, 2,400 GitHub stars, npm package at 52K weekly downloads. We want to raise a $12M Series A. Are we actually ready? What's the strongest way to position this, and what are we not seeing?
How it works
The data layer. SEC filings, accelerator directories, investor registries, traction signals — standardized, cross-referenced, and updated continuously. Free and open source.
Every conversation builds the dataset. Every raise that runs through it — the meetings, the passes, the ghosting, the terms, the close — becomes data. Not announcements. Not press releases. What actually happened, from the founder's side. That dataset doesn't exist anywhere else. And every raise makes the next one sharper: which investors actually write checks at your stage, how long they take, what makes them pass, and what makes them move — then calibrates on what actually worked, not what sounded right in training data.
Build on it. REST API and native integrations for LangChain, CrewAI, and Claude. Build fundraising intelligence into your product with a single call. x402 native — agents discover and pay autonomously, no key required.
The difference
Rearview mirror
—Pay $20K–$50K/yr to search a database
—Build your own target list in a spreadsheet
—Stale data — no idea who's deploying right now
—Same list your competitor is building
—You are the analyst
raise(fn)
—"Who should lead my Series A?" — 15 ranked matches
—Live data — who's deploying this quarter, not last year
—Flags your metrics are weak before you pitch
—Sequences outreach so the right investor moves first
—The analyst is built in
The flywheel
More founders raise → real outcome data
Every raise generates data no model can train on — who responded, who passed, who led, what terms closed. The Brain calibrates on results. That dataset doesn't exist anywhere else, and every raise that runs through raise(fn) makes it smarter for the next one.
More data sources → harder to replicate
SEC filings, accelerator directories, investor registries, traction platforms — each with custom ingestion, normalization, and cross-referencing logic. Copying one source is easy. Copying the intelligence that emerges from combining them is not.
Persistent context → switching costs
The Brain remembers your raise — metrics, investor conversations, pitch iterations. Walk away and you start from zero somewhere else.
Tool integrations → infrastructure lock-in
Once a product embeds raise(fn) for fundraising intelligence, it becomes infrastructure. Ripping out a working API is a cost nobody pays voluntarily.
The brain
Investor Matching
Ranked by actual fit — sector, stage, activity, check size. Not a directory.
Signal Reading
Decode investor behavior into actionable signals from real pattern data.
Term Sheet Intel
Market-rate terms for your stage and sector. Know where you have leverage.
Readiness Evaluation
Your metrics vs. projects that raised at your stage. Know where you stand.
Competitive Raise Intel
Who else in your sector is raising, at what valuation, with what traction.
Outreach Guidance
Who to contact, what angle, who can intro. Per-investor strategy.
Plus narrative analysis, valuation calibration, co-investor sequencing, pitch deck analysis, LP intelligence, and more.
The data layer
No AI model has this data. It doesn't exist in any training set.
It's live, it's comprehensive, and it's the foundation everything else is built on.
290+
Live sources
Real-time
No delays, no batches
Ground truth
The data AI models don't have
Built for
Founders raising
Know who to pitch, when you're ready, and what terms to expect. Use it for your raise, not forever.
Tools building
Embed fundraising intelligence in your product. One API, full raise coverage.
Investors deploying
Source deals, benchmark terms, track competitive dynamics, and monitor portfolio signals — all from live data.
Where this goes
Today
Founders use raise(fn) directly. The Brain knows your market, your investors, and your raise.
Tomorrow
Your AI assistant calls raise(fn) on your behalf. Same intelligence, agent-mediated.
The future
Agents raise capital autonomously. raise(fn) is the context layer the whole ecosystem runs on.
Get a free raise readiness assessment. No credit card required.