raise(fn) — Fundraising Intelligence for Startups
raise(fn)<br>Fundraising intelligence that gets smarter with every raise.
See it work<br>Ask a real question. Get a real answer.
raise(fn) brainlive<br>QWe'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<br>The tool founders never had. Now they do.
Layer 1<br>Eyes & Ears— How the Brain knows what it knows.<br>The data layer. SEC filings, accelerator directories, investor registries, traction signals — standardized, cross-referenced, and updated continuously. Free and open source.
OPEN SOURCE<br>Layer 2<br>The Brain— Fundraising intelligence for your raise.<br>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.
THE PRODUCT<br>Layer 3<br>Developer SDK— For tools that embed fundraising intelligence.<br>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.
OPEN SOURCE
The difference<br>Data platforms are rearview mirrors.<br>This is GPS.
Rearview mirror<br>—Pay $20K–$50K/yr to search a database<br>—Build your own target list in a spreadsheet<br>—Stale data — no idea who's deploying right now<br>—Same list your competitor is building<br>—You are the analyst
raise(fn)<br>—"Who should lead my Series A?" — 15 ranked matches<br>—Live data — who's deploying this quarter, not last year<br>—Flags your metrics are weak before you pitch<br>—Sequences outreach so the right investor moves first<br>—The analyst is built in
The flywheel<br>Every raise makes the next one smarter.
More founders raise → real outcome data<br>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<br>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<br>The Brain remembers your raise — metrics, investor conversations, pitch iterations. Walk away and you start from zero somewhere else.
Tool integrations → infrastructure lock-in<br>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<br>Fundraising intelligence, not guesswork
Investor Targeting<br>Ranked by actual fit — sector, stage, activity, check size. Not a directory.
Signal Reading<br>Decode investor behavior into actionable signals from real pattern data.
Term Sheet Intel<br>Market-rate terms for your stage and sector. Know where you have leverage.
Readiness Evaluation<br>Your metrics vs. projects that raised at your stage. Know where you stand.
Competitive Raise Intel<br>Who else in your sector is raising, at what valuation, with what traction.
Outreach Guidance<br>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.<br>See all 15 capabilities
The data layer<br>raise(fn) tracks every startup funding round in real time across 290+ sources.<br>No AI model has this data. It doesn't exist in any training set.<br>It's live, it's comprehensive, and it's the foundation everything else is built on.<br>290+<br>Live sources
Real-time<br>No delays, no batches
Ground truth<br>The data AI models don't have
Built for<br>Founders raising. Tools building. Investors deploying.
Founders raising<br>Know who to pitch, when you're ready, and what terms to expect. Use it for your raise, not forever.
Tools building<br>Embed fundraising intelligence in your product. One API, full raise coverage.
Investors deploying<br>Source deals, benchmark terms, track competitive dynamics, and monitor portfolio signals — all from live data.
Where this goes<br>From tool to infrastructure.
Today<br>Founders use raise(fn) directly. The Brain knows your market, your investors, and your raise.
Tomorrow<br>Your AI assistant calls raise(fn) on your behalf. Same intelligence, agent-mediated.
The future<br>Agents raise capital autonomously. raise(fn) is the...