Fraud infrastructure that can explain itself.
We build fraud-control infrastructure for financial institutions. Our conviction is simple: a fraud team should be able to move from local fraud knowledge to a live, explainable control without waiting on vendor cycles or trusting a black box.
A stronger control lifecycle for every institution.
Help fraud and compliance teams run the full loop: discover suspicious patterns, encode decision logic, test safely, deploy in real time, investigate with evidence, and improve controls over time.
Fraud isn't solved by a single model or a single dashboard. It's solved by institutions that can turn what they learn into governed controls, faster than attackers adapt.
Built from watching teams get stuck.
Loci started with a pattern we kept seeing: a fraud team spots a new scheme in the field, and then waits. Waits on a vendor change request, waits on an engineering sprint, or settles for an opaque score nobody can defend to an auditor.
Older monitoring tools were rigid. Black-box AI lacked the transparency regulated institutions need. So we built the layer in between: real-time decisions with model-like power, expressed in control logic that analysts, engineers, auditors, and regulators can all read.
Three rules we hold ourselves to.
Every decision decomposes into named signals with evidence attached. If we can't explain it, we don't ship it. "The model said so" is never the answer.
Our performance numbers come from benchmarks we can reproduce, not marketing math. When we can't evidence a claim, we don't make it.
AI drafts, discovers, and recommends. People decide. Production changes are designed to move through shadow testing and named approval on the record.
API-first fraud-control intelligence.
Composable primitives for real-time monitoring, explainable models, behavioral intelligence, screening, and governed investigation. Adopt one module or the full stack.
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