For traders and investors

Where whales do their research

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AI-native research workbench for traders and investors.

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agent@finwhale
You
Recalling how you judge peers
memorypeer_research · your saved preference
Memory
recalled how you judge peers rule weight reactions around corporate events — earnings first
Pulling candidates and ranking co-movement
sqlFront End Capital Equipment · 6 candidates · 90-session corr
Checking reactions on LRCX’s last prints
sqlearnings_calendar · ohlc_daily_split_adjusted · next session

AMAT and KLAC trade tightest with LRCX — 0.92 / 0.88 co-movement over 90 sessions — ranked with your rule: reactions around earnings count[1].

PeerCorr (90d)Jul 30 react
AMAT0.92+15.0%
KLAC0.88+6.0%
NVMI0.86+7.4%
UCTT0.82+19.6%

LRCX itself: +18.0% on 2026-07-30, the session after its Q4 print — EPS surprise +8.3%[2].

You
Finding the IPO prospectus
sec424B4 · SPACE EXPLORATION TECHNOLOGIES CORP · 2026-06-12
Extracting the lock-up terms
sec.lockup_termsunderwriting · shares_eligible · risk_factors
Result
form_type 424B4 · 3 cited spans searched underwriting, shares_eligible_for_future_sale, risk_factors
Sizing each tranche against traded volume
sqlohlc_daily_split_adjusted · SPCX · ADV since 2026-06-12

Up to 319.0M Class A shares release on 2026-08-20 — day 70 after the prospectus, and 2.6× the 124.9M average daily volume since listing[1].

ReleaseDayShares (up to)Tranche
2026-08-2070319.0M7%
2026-09-0990319.0M7%
2026-10-24135328.4M7%
2026-12-08180≤797.6Mremainder

Musk: 366-day lock-up to 2027-06-12, no early release[2].

Research
/sec$TICKERSEC filings — risk factors, MD&A, lock-ups, segments, 13F
/peer-research$TICKERPeers by how they actually trade — co-movement, events
/web-research$QUERYSearch the open web and read the pages it finds
System
/sql$QUERYPrices, returns, earnings dates, dividends and sector tags
/api$ENDPOINTCall a market-data endpoint directly
/document$FILERead an attached PDF, sheet or image
TICKER|
Ask anything, or press / for a skill↵ Send
What it is

A research partner that remembers.

FinWhale runs your research — filings, market data, the open web — and keeps what it learns. It remembers your calls, scores them against the market, knows when a thesis has gone stale, and opens each morning with what changed overnight.

Ask it

Ask what you’d ask a good analyst.

Every answer cites the filing or the data it came from.

And when the answer needs hours — a backtest, a data sweep — it runs the job and comes back.

Why it matters

Your edge is what you’ve noticed.

Most of it evaporates between sessions. FinWhale compounds it instead, session after session. You still call the trade.

What makes it different

The model isn’t the moat.

We run on the best models there are and get stronger as they improve. What a smarter model can’t manufacture is what accumulates here: your memory, and market data where every number shows its source.

Your best ideas die in notebooks. Here a hunch gets tested, remembered, and scored against what the market did next. Less a chatbot you re-explain yourself to every morning — more a brain that keeps score.
The partnership

We deploy into your desk.

Forward-deployed and founder-led. We learn how you actually work, then fit the workbench to it — past what ships in the standard product. Two or three firms a quarter.

Talk to the founder

Book a demo.

I’ll show you the workbench on live market data, and how a deployment would work for your desk.

Replies from the founder · Typical response, 24h