Maturity report
Shows what is observable, reviewable, missing, advisory, and not yet enforceable.
Repo readiness assessment for AI engineering governance
Assess whether your repo is ready for governed agentic delivery.
Reduce uncertainty before scaling AI-assisted development. Get a practical view of the governance gaps, evidence surfaces, and next steps needed to make AI-assisted engineering work observable, reviewable, and eventually enforceable.
Early assessments are currently assisted while the self-serve request flow is being prepared.
The gap
AI coding activity is moving faster than repo governance.
Engineering teams are adopting AI-assisted coding through everyday workflows, side channels, and experiments. The hard part is no longer whether code can be generated. It is whether leaders can see enough evidence, review structure, and delivery control to trust that work at scale.
A repo can have CI and code review while still missing the governance surfaces needed for agentic delivery: ownership, evidence packets, blocker classification, readiness states, and a clear implementation path.
What you get
A practical assessment, not a vague AI policy deck.
The assessment packages repo readiness into findings your engineering team can inspect, prioritize, and turn into governed implementation work.
Blocker classification
Separates missing governance surfaces from hardening items that can follow the first readiness pass.
Implementation-ready next steps
Turns readiness gaps into a path toward governed agentic delivery without claiming enforcement too early.
Assessment preview
Report/proof preview
This static preview shows how scattered AI coding activity can become evidence-backed delivery work. It is not live scan data and does not imply a repo has reached hosted enforcement.
Governance readiness snapshot
Sample repo assessment
Observed surfaces
Observed CI present, review workflow visible, baseline tests available.
Missing blockers
Missing Governed evidence packet and receiver-owned readiness record.
Advisory hardening
Ready to configure ready_to_configure Enforcement plan can be drafted after blocker review.
Application path
Ready to apply ready_to_apply Preview-ready only when implementation evidence exists.
Who it is for
Built for engineering leaders adopting AI coding tools where trust matters.
CTOs and technical founders
Get a credible path from AI coding experimentation to accountable delivery.
VPs and Heads of Engineering
Find uneven practices, unclear review expectations, and governance gaps before they scale.
Trust-sensitive software teams
Make AI-assisted work easier to review, defend, and improve without claiming automation that is not live.
How it works
Start with assisted readiness before enforcement claims.
Review the repo context
Assess the current verification, review, evidence, and governance surfaces.
Classify blockers and advisory findings
Separate must-fix readiness gaps from hardening items that can follow.
Map the implementation path
Define what can move toward `ready_to_configure`, what can become `ready_to_apply`, and what is not enforced.
Built this way
Built on the same governed operating model it helps you adopt.
Operating model
The product is being built through staged governed work with prompts, run logs, verification evidence, and explicit review boundaries.
Proof and planning
Explore remains the proof/reference surface while Bootstrap performs assessment and governance planning.
Portable contracts
Kernel preserves portable contract semantics for future implementation work.
Customer surface
This GTM app turns that work into a customer-facing assessment journey without claiming full integration in V0.
Current-stage honesty
Clear limits make the assessment more trustworthy.
V0 is intentionally narrow. The homepage explains the offer and preview shape while the workflow remains assisted and evidence-led.
- Early assessments are assisted.
- The GTM app does not yet provide self-serve repo scanning.
- This page does not claim hosted enforcement.
- The product does not mutate receiver repos in V0.
- Bootstrap and Kernel remain the underlying governance implementation systems.
Next step
See what your first assessment would cover.
Review the static assessment preview and current-stage notes; early assessments remain assisted while the self-serve request flow is prepared.
This page previews the assessment shape; it does not provide self-serve scanning, GitHub connection, assessment execution, receiver repo mutation, or hosted enforcement yet.