Solutions
Autonomous trading agents
Agents trade continuously, at machine speed, with no instinct for when a market has gone thin. Speed without depth awareness is not an edge — it is a liability that compounds every block.
What you get
- One call before every order, priced per request
- Agent-native JSON, not a human dashboard
- Sub-second response target
The panel beside this shows the shape of the answer, not live data. Three things are in production today — depth recording, keyless verification and the published method. Everything else is roadmap and is labeled as such.
Other solutions
- Lending protocolsYour liquidation engine marks collateral at oracle price and unwinds it at book price. The difference is an unmeasured short position in liquidity, carried on every loan.
- Tokenized equities and RWAThose markets close. The tokens never do. An agent trading a tokenized stock on Saturday is quoting Friday's price into an empty book, and nothing in its stack tells it so.
- Treasuries and DAOsA treasury dashboard multiplies balance by oracle price and calls it a valuation. It is a valuation at zero size. The number that matters is what the treasury clears at when it actually needs the cash.
- Quant desks and market makersYou already model execution internally. Crifine is the outside check — an independently recorded depth series, with the assumed size and observation window stated, that your model can be scored against.
- Risk platformsParameter reviews answer whether a protocol's settings are sound. They run quarterly, per protocol, for humans. Crifine answers the same question per order, per moment, for machines.