Autonomous execution, full governance.
WIDTH's agents reason across every data signal you onboard — identity, behaviour, transactions, networks. Every decision is explainable, every action reversible, every trace auditable.
WIDTH's agents reason across every data signal you onboard — identity, behaviour, transactions, networks. Every decision is explainable, every action reversible, every trace auditable.
Three loops, working in parallel, on every customer and every event. No hand-offs, no lost context.
The reasoning loop ingests KYC data, transactions, device signals, and network context — then updates the customer's risk graph continuously. Human analysts see the same graph, annotated with the AI's current hypotheses.
Explore the graph →
Every action the AI takes — clear, hold, escalate, file SAR — is bounded by your written policy.
See policies →Plain-English rationale for every flag, with cited evidence and rule references.
See a sample →The AI auto-clears low-risk, auto-holds obvious hits, and routes genuine ambiguity to analysts.
How cases work →Every model change is logged, reviewable by your risk committee, and reversible.
See governance →Most compliance vendors wrap an LLM around a legacy rules engine. The result: faster guesses, harder-to-explain outcomes, and regulators that cannot be satisfied.
For the first time, we can walk a regulator through a decision and cite the exact feature, model version, and policy rule that produced it — in under sixty seconds.
30 minutes. We'll walk a real decision end-to-end — data in, reasoning, policy match, human review, audit trail out.