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Architecture maps your codebase into named features and shows how work distributes across them. It also powers the architecture multiplier that adjusts performance scores based on structural complexity.

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Feature discovery

When architecture analysis is enabled, Navigara runs a multi-phase AI agent per repository that:
  1. Explores the codebase structure to discover distinct features (e.g. auth, billing, notifications).
  2. Organizes each feature into vertical layers — frontend, backend, and data — with specific file paths.
  3. Maps dependencies between features, showing which parts of the system are coupled.
The agent produces a feature graph: nodes are features with known layers, edges are dependency relationships. This graph is used for both visualization and as input to the performance multiplier.

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Commit-to-feature matching

Once features are discovered, every commit is matched to the feature(s) it touches based on the files it changes. This uses path-based scoring: When a file belongs to multiple features (e.g. a shared utility), the match is weighted to avoid double-counting.

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Repository mesh

When multiple repositories are connected to the same organization, their feature graphs are stitched into a repository mesh — a cross-repo dependency map. The mesh emerges from API contracts, shared libraries, and event flows detected by the architect agent. See Performance > Repository mesh for how the mesh affects scoring.

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What you see

All performance and alignment metrics can be grouped by feature, so you can answer questions like:
  • Which features are getting the most investment?
  • Where is most of the bug-fix work concentrated?
  • Is the auth system seeing unplanned churn?
  • Which features have the highest structural complexity?
  • Where do cross-repository dependencies create leverage?
Architecture analysis is optional and can be enabled per repository. It’s most useful for larger codebases where work naturally spans multiple distinct areas.