AI Agent Governance

Scale AI agents without losing control.

Govern agentic development by code impact, review depth, quality, and spend — and decide where to expand, monitor, or restrict.

Book a Demo See Agent Observability →

The Governance Gap

Let agents move
fast.Keep engineering in control.

Activity is easy to generate.Control over where it lands is not.

Agents already commit, open PRs, and reshape your codebase. Without governance, adoption becomes unmanaged automation — with no view of where agents add risk or where human judgment must stay in the loop.

Invisible autonomy
Weak review discipline
Spend drift
Quality debt

Agent Governance

See which agents to scale,
and which to hold back.

Rank every agent by contribution, acceptance, and impact — each with a recommended posture grounded in real engineering signals.

Contribution Rate

Share of work each agent ships

Acceptance Rate

How much of the output is kept

Autonomy Level

How much runs unsupervised

Turn governance into an operating system.

Move from passive monitoring to active control — see what to scale, what needs guardrails, and what to pause.

Policy Matrix

Set the right control for every agent workflow.

Not every workflow needs the same control. Apply governance by real engineering signals — not blanket rules.

Agent workflowRiskMilestone signalGovernance

Boilerplate generationLowHigh survival · low reviewAllow broad usage

Test creationLow–medImproves coverage · low reworkExpand with monitoring

Bug fixesMediumFaster cycle · mixed reworkRequire reviewer validation

RefactoringMed–highLarger PRs · architecturalRequire senior review

Security-sensitive codeHighSensitive · high-risk repoRestrict or require approval

Legacy core changesHighHigh rework / revert rateLimit autonomy · guardrails

Sample governance signals · product UI

Spend Governance

Connect agent spend to
real engineering output.

Tie licenses, tokens, and autonomous runs to the output they produce — and govern with confidence.

Cost / merged PR

$0

22% lower QoQ

Spend / developer

$0

412 active seats

Reclaimable / mo

$0

41 idle seats flagged

Return on AI spend

0x

value returned / dollar

Sample dashboard metrics · product UI

Review Governance

Keep humans in
control
where judgment
matters.

Track whether senior engineers are genuinely reviewing agent work — where review load is rising and where agent PRs need extra correction.

–0%

Review depth · agent PRs

0%

Senior involvement

+0%

Post-review changes

0%

Code survival · 30d

Agent PR · Governed Lifecycle

1

Agent Contribution

Agent pushes code; Milestone tags repo, workflow & risk

2

Policy Check

High-risk path → senior approval required before merge

3

Human Review

Senior engineer reviews; depth tracked, not rubber-stamped

4

Merged & Tracked

Ships with attribution; survival & rework monitored

Executive Intelligence

The answers leaders need to scale AI responsibly.

Governance pays off when it drives better allocation decisions.

Scale

0

agents ready to expand

Reinforce

0

412 active seats

Reclaim

$0K

41 idle seats flagged

Restrict

0

value returned / dollar

Aligned

0%

work on roadmap

Platform Ecosystem

Connect your entire engineering stack.

Native integrations with every tool in your AI engineering workflow — from coding agents to repositories to project management.

GitHub GitLab Bitbucket Claude-Code Cursor Copilot Jira Linear Slack Datadog

Repositories

GitHub

GitLab

Bitbucket

Project Systems

Jira

Linear

Signals

Slack

Datadog

AI Agents

Claude-Code

Cursor

Copilot

MILESTONE

Engineering Intelligence Layer

AI Adoption

Who uses which agents — and how deeply.

Spend + ROI

Cost per agent against measurable output.

Quality + Governance

Code health, risk, and policy at a glance.

Get Started

AI-native engineering needs governance.

Scale agentic development with the right balance of autonomy, oversight, quality, and spend discipline.

Book Demo Explore Agent Observability →