The desk that never sleeps.

Counts the trials behind your backtest, adjusts for skew and kurtosis, and returns the Deflated Sharpe Ratio — the only number that should leave your desk. A 2.5 Sharpe from 100 tries is usually a coin flip; it tells you so.

Combinatorial purged cross-validation gives you a distribution of Sharpe ratios across hundreds of train/test splits — with purging and embargoing so serially-correlated labels can't leak. One walk-forward path is an anecdote.

PBO via CSCV — the probability your in-sample winner lands below the out-of-sample median. Above 5% and none of your variants are real. You hear it before you commit capital, not after.

Point it at a factor paper and it re-implements the signal, runs it on your universe, and tells you whether it survives out of sample — the Chen-Zimmermann workflow, on demand.

Dollar bars over time bars, fractional differentiation that keeps memory while reaching stationarity, triple-barrier labels scaled to volatility. The unglamorous data work that decides whether a model can learn anything.

Every proposed strategy comes with the mechanism — who is making the systematic mistake you get paid for. An edge with no falsifiable reason is flagged as likely false.

Market data, macro prints, news, social, on-chain — pulled, aligned, point-in-time correct, and stored in your own container. No survivorship bias, no look-ahead.

Knows the difference between when a number was released and when it was revised. The leak that quietly inflates every naive backtest never enters yours.

Scheduled refreshes, schema checks, gap detection — with a daily one-line health summary on your channel. The pipeline is the product, and it treats it that way.

Decision price vs fill price — the benchmark that tells the truth, not VWAP, which your own algo can game. Every parent order decomposed into impact and opportunity cost.

Reads the trade log, separates permanent (information) impact from transient (noise), and shows you which fills were adverse selection — Kyle's lambda, estimated on your own flow.

Front-load when volatile, slow down when calm — the Almgren-Chriss cost-vs-variance frontier, applied to your actual order sizes and your actual risk aversion.

Hourly SSH into your trading box, log-tail for errors, watches inventory, drawdown, and adverse-fill spikes — a daily one-line health summary on whichever channel you live in.

Stuck orders, a stale feed, a drawdown breach, latency creep — the alert lands on Slack, Discord, or iMessage. Text STOP from your phone and the kill switch fires from anywhere.

Reads the trade log after a bad session, finds where the book got run over, and proposes parameter changes with the reasoning attached — analyst work, not a chatbot's guess.

Position caps, daily loss limits, portfolio drawdown circuit breakers — the rules hold at 3am, on tilt, and after a good week, which is exactly when you most want to override them.

Rolling 60-trade edge below zero, three losses on one archetype, a drawdown breach — the strategy stops. It does not tune it more or give it another month; the literature is clear that is how quant projects die.

Tracks whether live conditions still match the data-generating process your strategy was certified on. When the distribution shifts, you hear about it before the P&L does.