INDEPENDENT CONTROL PLANE FOR ENTERPRISE AI
Cynsta helps enterprise teams gate risky AI changes before deploy, authorize high-risk actions during runtime, and keep independently verifiable evidence after every incident or review.
Baseline agent behavior, compare changes in CI, and stop riskier releases before production.
Allow, block, rate-limit, or require approval for high-risk actions when agents touch real systems.
Export portable AAP records for incidents, audits, insurer reviews, and internal investigations.
OpenTelemetry-native capture for OpenAI, Anthropic, LangChain, custom agents, and existing telemetry stacks.
Cynsta starts with release assurance, expands into action authorization, and ends with evidence any auditor, insurer, or security team can verify independently.
Cynsta observes outside the critical path, then feeds release and runtime controls with action-level context. No gateway. No proxy. No new single point of failure.
Instrument tool calls, arguments, approvals, and outcomes through OTEL so Cynsta sees what the agent is actually trying to do.

Run collectors and sidecars outside the hot path. Buffer locally, retry safely, and avoid a new latency dependency.

Every record is normalized, hashed, and packaged into reviewable evidence artifacts without changing how engineering teams work.

Keep using Langfuse, Datadog, or internal pipelines. Cynsta fits beside your current telemetry instead of replacing it.

Start with release visibility, then add approval flows, runtime authorization, and review workflows as systems become higher risk.

Start with systems that can grant access, move money, change records, or route regulated work. Cynsta is built for teams shipping action-taking AI into production.
Do not see your workflow here? We work with any AI system that can approve, modify, spend, route, or reach systems of record.
See detailed use casesProduct status
Release Gate and the AAP trust layer are already part of the product. Runtime Authorization is the active buildout for teams that need inline policy, approvals, and step-up control on high-risk AI actions.
Baseline agent behavior, compare changes in CI, and stop riskier model, prompt, or tool changes before they ship.
Portable evidence, verifier-backed review artifacts, and third-party trust for incidents, audits, and insurer workflows.
Add allow, block, approval, and step-up control flows for privileged actions, external destinations, and spend.
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