Streaming decisions, risk scoring, and observability—at millisecond speed.
Our event-driven engine ingests device, network, and identity signals; enriches them with watchlists and behavioral context; and evaluates adaptive policies backed by ML. Feature stores keep user, device, and session attributes fresh for sub-second lookups, while champion/challenger testing lets you iterate models safely. Every decision produces signed, time-stamped evidence for audit and model governance.
Complex event processing and real-time rules to approve, challenge, or block within milliseconds.
ML models blend device, behavior, and identity signals into explainable scores and reasons.
Low-latency profiles for users/devices/sessions with versioned features and time-travel queries.
Risk-based step-up (liveness/doc), fallbacks, and escalation paths by market, product, or channel.
Queue high-risk cases with priority SLAs and route to reviewers with dual-control options.
Dashboards, latency/error budgets, drift alerts, and evidence reports for audits and model reviews.
Signals flow through ingestion, enrichment, policy evaluation, and model scoring. The result is a decision with explanations, a signed log, and optional callbacks via webhooks or message topics. Scale elastically under peak loads with consistent latency.
Govern the full model lifecycle with versioning, approvals, and rollback. Validate performance online with A/B and champion/challenger. Detect drift early and trigger retraining pipelines. Produce evidence for internal committees and regulators.
Synchronous scoring endpoints and async webhooks for decisions, alerts, and case events.
Publish/subscribe topics for high-throughput use cases and back-pressure resilience.
OAuth2/OIDC, mTLS, scoped tokens, and per-tenant limits with detailed audit trails.
Decisions you can trust—instantly.
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