Control risky AI actions before they ship or execute.

We work with a small set of design partners building AI that can access tools, move work, and touch systems of record.

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Supported by EuroHPC Joint Undertaking (AI Factory Fast Lane), Leonardo (CINECA), and E2B for Startups.
EuroHPC Joint Undertaking logoLeonardo and CINECA logoSponsored by E2B for Startups
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Release Gate

Baseline agent behavior, compare changes in CI, and stop risky releases before they ship.

Runtime Authorization

Allow, block, rate-limit, or require approval for high-risk AI actions in production.

AAP Evidence

Export portable evidence and review packets that third parties can verify independently.

Identity & IT Operations

Privileged tools, admin changes, and runbook automation.

Payments & Finance Ops

Beneficiaries, approvals, transfers, and exception handling.

Support & Back Office

Refunds, CRM updates, and systems-of-record workflows.

Healthcare Operations

Triage, documentation, and regulated operational workflows.

Insurance Operations

Claims intake, extraction, and adjudication support.

Public Sector Casework

Routing, eligibility support, and citizen-facing workflows.

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About Cynsta

The independent control plane for enterprise AI

Cynsta helps teams decide whether AI is safe to ship, allowed to act, and able to prove what happened later.

We are building the independent control layer for enterprise AI systems that can take action. Cynsta starts with release assurance, expands into runtime authorization, and ends with verifiable evidence any reviewer can inspect without trusting our UI.

Our platform connects to any AI stack via OpenTelemetry: OpenAI, Anthropic, LangChain, or custom models. No code rewrites needed. The same control and evidence layer supports engineers, security, and risk teams as AI moves from recommendation into execution.

Release
Baseline agent behavior before it reaches production
Runtime
Allow, block, and approval flows for risky actions
AAP
Portable evidence for incidents, audits, and review
Independent
Observer architecture with no gateway lock-in
Cynsta label

The team

Cynsta grew out of work on AI reliability, evidence, and deployment infrastructure. We kept seeing the same gap: teams could demo AI, but they could not govern risky changes and actions with the rigor they already expect from software releases.

We are a product-focused team based in Prague with collaborators across the EU and US. We ship fast, stay close to engineering and security buyers, and build for the workflows where AI can grant access, move money, change records, or route regulated work.

If you want to help define how enterprises control action-taking AI, take a look at our open roles or email us at hello@cynsta.com.

Our mission is to make enterprise AI controllable. That means catching risky changes before deploy, enforcing policy on high-risk actions during runtime, and keeping independent evidence for incident review afterward.

We are pragmatic about how adoption happens: release assurance first, runtime authorization next, evidence and review as the trust layer. The goal is not another dashboard. It is a control system teams use every time AI touches something important.