The AI governance platform that tests before you ship, monitors what's live, and enforces policy in real time. Audit-ready evidence comes standard.
See what full control looks like
Openlayer
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Copilots, agents, and models are going to production across every business unit. Most companies can't list them, few can test them, and almost none can prove to a regulator what any of them did last Tuesday.
88%
of AI agents built never make it to production due to governance and eval gaps
Source: S&P Global, 2026
79%
of enterprises do not have a governance model for the AI agents they are already running
Source: McKinsey, 2026
$207M
is the average projected AI spend per US enterprise over the next 12 months
Source: KPMG, Q1 2026
Each layer delivers value on its own. Together, they turn scattered AI into systems you can govern, observe, and prove are under control.
Know what
AI you have
Know every AI system running, org-wide inventory and automatic shadow-AI detection.
You can’t govern what you can’t see, so this is where control begins.
Catalog and
assess risk
Turn a raw inventory into an accountable registry.
Register each system with its owner, purpose, data sensitivity, and risk tier using intake and risk-assessment forms you build to fit your policy.
Catch problems
before they ship
Build evaluation suites and run them pre- and post-deployment against your own data.
Benchmark every change and block regressions in CI, so quality is proven rather than hoped for.
See what your AI
does in production
Trace every input and output. Monitor quality, cost, latency, and drift on live traffic, and get alerted the moment behavior changes — across apps you build and tools you buy.
Protect AI in
real time
Protect AI in real time. Block prompt injection, jailbreaks, PII and PHI leakage, and off-policy outputs before they reach a user.
Enforce access and routing policies at the gateway, so every request is governed, not just watched.
Map frameworks and
prove compliance
Map everything to the frameworks you answer to: EU AI Act, NIST AI RMF, ISO 42001, and your internal policy.
Compliance isn’t a separate workstream, it’s powered by every layer beneath it.
Know and
control spend
Know and control spend, token spend by project, team, and user, hard budget caps per API key or team, usage dashboards for finance and leadership, ROI visibility that ties spend to outcomes.
6x
Faster from development to deployment
90%
Reduction in audit preparation lift
53%
Higher throughput withOpenlayer
100%
Client renewal rate
Every major LLM provider. SDKs, CLI, REST API, Git, OpenTelemetry, and Snowflake. Vendor AI, homegrown agents, and classic ML, governed the same way.
Capability
Code you own
Traffic you can route
Connected vendor AI
Opaque vendor AI
Discover
Registration
Testing
Observation
Security & Guardrails
Compliance
Openlayer is the AI governance platform that helps enterprises build, deploy, and operate trustworthy AI systems. It gives teams one place to discover, test, monitor, govern, and optimize every AI system they run.
Most organizations run AI systems that were never formally tested, are not continuously monitored, and cannot prove policy was actually enforced. Openlayer gives every AI system, built in house, purchased, or embedded in a vendor tool, a single place to be discovered, tested, watched, and governed.
Observability tools show what already happened. Openlayer also tests systems before they reach production and enforces policy while they run, so governance evidence is generated continuously as part of normal operations.
The platform is organized around seven layers: Discovery, Registration, Testing, Observability, Guardrails, Compliance, and Cost Controls. The Gateway sits across these layers as the enforcement point, giving teams one place to route, monitor, and control AI traffic without rewriting applications.
Openlayer covers large language models, retrieval augmented generation pipelines, autonomous agents, traditional machine learning models, and multimodal systems, whether they were built internally or purchased from a vendor.
Openlayer connects through SDKs, framework integrations, a network level gateway, a CLI, and a REST API. Most teams instrument their existing stack directly, without a significant rewrite of their applications.
Engineering and AI teams use Openlayer to test and monitor models day to day. Security, compliance, and finance teams draw on the same underlying data to enforce policy, prepare for audits, and track AI spend.
Openlayer helps teams shorten testing cycles, catch production issues earlier, automate governance evidence, reduce manual compliance work, and gain clearer visibility into AI risk and spend.
Openlayer is purpose built for regulated enterprises in industries such as insurance, financial services, telecommunications, and healthcare, where a wrong AI output carries real financial, security, or regulatory consequences. The platform is SOC 2 Type II certified.
Most teams start with the free Basic plan, connect a project through the SDK or gateway, and run the pre-built test library against a model or agent. Enterprise teams typically begin with a guided onboarding call.
See one AI system tested, monitored, and governed from end to end.
No Risk
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