Applied AI
AI that assists analysts — and never decides for them.
The AI layer accelerates investigations and drafts regulator narratives. But every screening outcome stays deterministic, rule-traceable, and human-owned. The agents are tools — the analyst is in charge.
“Agents are tools analysts use — not decisions the system makes.”
Screening BLOCK / REVIEW / ALLOW and case dispositions stay deterministic and rule-traceable. The agent trace exists to prove the AI didn't decide — which is exactly what a compliance buyer needs to hear.
On-prem & model-agnostic
Agents run against open models in your environment behind a model-agnostic interface — no third-party LLM ever sees counterparty data, and the model is swappable per agent.
Grounded, or it abstains
Answers are grounded in your knowledge base and cite their sources; a hallucination guard rejects ungrounded figures and falls back to a deterministic template. The copilot would rather say 'not found' than guess.
Adaptive matching
ML-assisted matching lowers false positives over time, learning from analyst decisions — rolled out shadow → canary → live behind a KPI guard with automatic rollback.
Human-in-the-loop by design
Every consequential agent action is proposed, not performed — a human approves it (with four-eyes where it matters), and the whole exchange is written to an immutable agent trace.
Security-first AI
An agent tier built to an explicit security baseline.
Least-privilege tool access, prompt-injection defenses, output validation, sandboxed and gated operations, and complete traceability — aligned to the OWASP LLM Top 10. AI capability that a security review can actually pass.