tickfoundry
capture livesign inget the data →
§ use-cases

What people build with
tick-level prediction-market data.

The same captured tape — every order, every book update, every fill — feeds a wide span of work, from a solo backtest to a desk's reproduction audit. Each job below shows the data layer it needs and the plan that unlocks it.

01

Backtesting & signal research

Every print and every top-of-book move, in arrival order, with nanosecond receive timestamps. Replay a strategy against the real tape — no resampled candles, no survivorship gaps — and measure edge against what was actually quotable at the touch.

L1 + tradesevery tickExplorer+
Load & join in pandas →
02

Market microstructure & slippage

Walk the full 25-level L2 ladder to size a fill the way the book really clears. Reconstruct VWAP against resting depth, study queue dynamics and book pressure, and cost a strategy honestly instead of assuming touch-price fills.

full 25× L2ladder + VWAPPremium
Worked slippage example →
03

Whale & smart-money tracking

Onchain trade fills carry the settling transaction_hash, so every print joins back to a wallet. Follow large or repeat actors across markets, cluster cohorts, and study how informed flow leads price — with onchain trade history back to July 2025, backfilling toward each market's inception (~3 years).

onchain fillstransaction_hashExplorer+
See trades schema →
04

Crypto spot × prediction-market correlation

The Binance and Chainlink spot (RTDS) feeds ship aligned with Polymarket on the same receive clock. Quantify how spot moves lead — or lag — the implied probability on crypto markets, and build cross-asset signals on a single timeline.

Binance + Chainlink (RTDS)cross-assetPremium+
See pricing →
05

Liquidity & market-making studies

Full-depth snapshots expose resting size at every level, spread regimes and how the book refills after it's swept. Model adverse selection, inventory risk and quoting behaviour across the whole venue rather than a single market.

full depthresting size · spreadsPremium
See L2 schema →
06

Event-driven & news-reaction research

Each row carries the collector's nanosecond receive timestamp, so you can measure reaction latency to the tick. Anchor on a resolving event or a headline and watch the book and tape respond in real, replayable time.

ns receive tsreaction latencyExplorer+
Book at time T →
07

ML training datasets

Pull at scale over the REST API or SFTP — clean, columnar parquet with stable schemas and join keys, ready to stream into a training pipeline. No scraping, no normalization, no per-market plumbing to maintain.

REST API / SFTPclean parquetPremium / Enterprise
API reference →
08

Reproduction & audit

Raw websocket atoms plus the deterministic replay engine let you rebuild any book at any nanosecond, in-house, byte-for-byte. The provenance trail funds and auditors need when a number has to be defensible.

raw atomsdeterministic replayEnterprise
Data quality →
live
Research case studies

Reproducible studies computed from the same parquet bundles we sell, so you can rerun every result yourself. First up: Spain–Belgium's last-minute winner — a 62-point repricing in 0.65 seconds, a 31¢ spread blowout, and the depth collapse behind it.

Read the study →All research
Pick the plan that fits the job, or pull one market·day to try the shape.
See pricing →Download a sample →