# Every AI system in your company. In one place. Under control.

The AI governance platform that tests before you ship, monitors what's live, and enforces policy in real time. Audit-ready evidence comes standard.

## Your teams are shipping AI. Your controls are not keeping up.

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.

| Stat | Meaning |
| --- | --- |
| 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) |

## Control your AI, layer by layer.

Each layer delivers value on its own. Together, they turn scattered AI into systems you can govern, observe, and prove are under control.

### Discovery

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.

- Org-wide AI system inventory
- Integrations with all major ADKs
- Automatic shadow-AI detection

### Registration

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.

- Central AI registry
- Custom intake forms and lifecycle management
- Model and dataset versioning
- Risk assessment and tiering

### Testing

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.

- 175+ out of the box evals
- Regression testing
- CI/CD testing
- Diagnostic tools and root cause analysis
- Custom metrics

### Observability

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.

- Monitoring for every deployment
- Trace prompts, responses, tool calls, and more
- Continuous online evaluation
- Diagnostic tools and root cause analysis

### Security and Guardrails

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.

- Real-time control and guardrails at every step
- PII detection and redaction
- Policy enforcement and gateway routing
- Custom guardrails and content safety
- Prompt-injection and jailbreak defense

### Compliance

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.

- Framework mapping (EU AI Act, NIST, ISO 42001)
- Control libraries
- Audit-ready evidence
- Controls for internal and external frameworks
- Reporting and attestations

### Cost Controls

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.

- Token spend by project, team, and user
- Hard budget caps per API key or team
- Usage dashboards for finance and leadership
- Protect against security flaws and vulnerabilities as they arise
- Automatically route high-spend users to cheaper models
- Avoid downtime when models go dark
- Tie spend to outcomes and surface projects with no measurable return

## What people are saying

> We were tracking 120 concurrent AI projects in SharePoint. It was not live, not connected to anything, and we had no way to know what any of them were actually doing.
>
> Head of AI, Major Hospital Group

> We have 80 AI tools, half from vendors, half internal. We have a governance council but no continuous monitoring. That is the gap we need to close.
>
> AI Governance Lead, Enterprise Financial Services

> We can finally prove oversight without slowing down engineering.
>
> Chief Risk Officer, F500 Global Insurance Firm

> We have intake, but governance is still evolving. That's the hair on fire problem. We needed something that connects them.
>
> Head of AI Governance, Regulated Financial Services

## By the numbers

| Stat | Meaning |
| --- | --- |
| 6x | Faster from development to deployment |
| 90% | Reduction in audit preparation lift |
| 53% | Higher throughput with Openlayer |
| 100% | Client renewal rate |

## Works across every AI source

Every major LLM provider. SDKs, CLI, REST API, Git, OpenTelemetry, and Snowflake. Vendor AI, homegrown agents, and classic ML, governed the same way.

## Ship with confidence.

See one AI system tested, monitored, and governed from end to end.