Instrument
Drop Sengol into your AI pipeline. It captures every model input, output, score, and decision automatically. Zero config. Works with any agent — LLM, RAG pipeline, or traditional ML model.
Responsible AI governance platform
Build without fear.Govern without friction.
Sengol runs silently underneath your AI — capturing every decision, every evaluation, and every model action — so your teams ship fast while risk leaders get the confidence they need.
Request Early AccessResponsible AI · Safe deployment · Signed evidence for risk management
The organizations moving fastest on AI are converging on the same truth: responsible AI needs runtime controls, traceability, documentation, and proof. Written policies do not keep production agents inside their accepted boundaries. Sengol turns safe AI governance into enforceable controls and evidence your business can trust.
Your engineers want to ship.
Your risk team wants proof.
Your business wants both.
Sengol is the reason you can say yes to all three.
The trust stack needs evaluation and control.
Evaluations tell you whether an agent behaved safely. Runtime controls decide what happens next: allow, warn, block, escalate, or record the action for review.
Sengol connects both sides. Policy, telemetry, decisions, and signed evidence move together so teams can understand not just what an agent did, but why it was allowed to do it.
Know when agents drift.
Keep them inside their approved boundaries.
How it works
Policy and evidence finally travel together — from risk requirement to production control, automatically.
Evaluate
Deterministic and LLM-backed evaluators run on every inference. Fairness. Drift. Hallucination. PII. Outcome monitoring. Every result signed and timestamped with a tamper-evident HMAC chain.
Prove
Show which controls ran, what each agent did, and why every action was allowed, blocked, or escalated. Create signed evidence for any agent, any workflow, and any period — without relying on screenshots or spreadsheets.
Who it's for
Deploy AI in production with confidence — while giving every stakeholder the proof they need.
Chief Risk Officer / Head of Model Risk
When the business asks whether agents are operating within accepted risk boundaries, Sengol is how you answer. Signed audit trails. Control-level evidence. A tamper-evident record that stays intact overnight.
VP Engineering / ML Platform Lead
Integrates in a sprint. Runs in your CI/CD pipeline. Blocks a failing deploy before it ships. Works with your existing OTel stack. Your engineers never slow down to prove they were responsible.
Compliance Officer / Model Risk
Every AI agent response is evaluated, signed, and checked against declared controls. Generate evidence on demand for any agent, any workflow, and any period.
Why Sengol
Sengol is not another dashboard. It is the control and evidence layer for responsible, safe AI in production.
Obligation-depth governance
Map production controls to your risk requirements, safety policies, model standards, and operating procedures — then keep evidence tied to the exact control that ran.
Tamper-evident evidence chain
Every evaluation is HMAC-SHA256 signed and append-only. If a record changes, you know. Your risk team knows. That is what makes it evidence.
Governance in your CI/CD gate
Sengol blocks a failing deploy before it ships and keeps watching after release. Responsible AI becomes part of production operations, not a meeting after something goes wrong.
Open core, inside your perimeter
Apache 2.0 SDK. Deploy inside your own VPC. No data leaves your infrastructure. Privacy, security, and data residency expectations are easier to satisfy by design.
From continuous production to controlled agents.
Register
Evaluate
Gate
Monitor
Certify
Prove
Every step is a CLI command, an API call, and a signed record — from pre-deploy gates to live agent monitoring.
Your teams ship.
Sengol keeps agents in bounds.
Declare your controls. Sengol makes them executable, verifiable, and defensible in production.