Your product, as a living map of the code beneath it.
Dynvo maps every feature from git history, scores it by health, risk and coverage, then overlays live Sentry errors and PostHog usage — so you see what breaks before your users do. No SDK. No instrumentation.
You ship features —
then lose the map.
Dashboards grade lines of code. Error trackers list stack traces. Neither tells you, per feature: is this healthy, is anyone using it, and what breaks if I change it?
Invisible risk
You find out a flow is broken when a customer tells you — errors arrive as traces, not features.
Dead weight
Code nobody runs still has to be maintained, tested and reasoned about. You can’t cut what you can’t see.
Blast radius
Before an edit — human or agent — nobody knows the real reach. Reviews drag; regressions slip.
From your code to a skill-map of your product.
Four layers, one scan. Each diagram on the right is a live 3D model of that layer. See it on a real scan →
Your code & infrastructure
Services, gateways, queues, datastores — the real architecture in your repository, exactly as it’s wired together. This is the ground truth we read.
What your users actually get
The product as people use it — features become districts, and the flows users travel between them become the roads of a living city.
One scan maps code to product
The membrane between the code and the city. A scan line sweeps the whole repository and reconstructs the map — this is our integration, doing its work.
A skill-map of your product
Product features and user flows, each scored. Feature names surface over the city; red hotspots flag what needs attention or a refactor; little carts are live PostHog traffic mapped onto features — so you see where the activity, and the risk, really is.
Mapped through the scan live at that commit — runtime lands on the map, not in a separate dashboard.
One scan from git history. A map for your team and precise context for your AI agent.
We read your repository’s history — not a README, not an SDK — and reconstruct the features, the flows inside them, and the files each one touches. Then we score every feature and attach your runtime signal.
Product, on top
Each district is a product feature; the tower is the feature, the buildings are its developer features, the roads are the flows users travel.
The scan, in the middle
The glowing membrane is the product — the scan that maps the code below into the city above. Its cracks are where risk concentrates.
Real system, underneath
Services, gateways, queues and datastores — the actual architecture. Alignment beams prove every feature is grounded in real code.
Health · risk · churn · coverage
Bug-fix ratio, hotspots, ownership and test coverage — per feature and per flow, so risk stops being invisible.
Sentry errors · PostHog usage
Live runtime signal mapped onto the map — what’s breaking, what nobody touches — no SDK, no instrumentation.
Context for your AI agent
The same map an engineer reads becomes precise, structured context an agent can query over MCP before it edits a line.
Your code stays yours.
Dynvo reads git history to build the map — it doesn’t need to keep your source code at rest. Encrypted in transit, least-privilege access, and a clear data-flow you can audit.
Read the security page- No source code stored at rest
- Encrypted in transit · KMS-backed secrets
- Read-only git access, least privilege
- MIT-licensed open-source engine