One memory of your codebase, three ways to use it
Your senior engineers lose hours to the Review Grind, the same first-pass checks on every pull request. Heedvane takes that first pass, built on one memory of your whole codebase. Your seniors step in only where judgment matters.
Most teams don't have a code quality problem. They have a senior-engineer bandwidth problem.
Everything here is built to give that bandwidth back.
The same memory, three ways to use it
Not three tools to stitch together. One memory of your codebase, doing three different jobs.
The PR reviewer
Every pull request reviewed against the memory of your whole codebase, before a human opens it.
The knowledge base
Living documentation that stays current as the code changes, with drift detection when it falls behind. Grounded chat, search, and ownership maps are on the way.
Security & compliance
Continuous checks mapped to the standards you answer to, with an audit trail you can export.
One memory of your whole codebase
Shared by all three surfaces. A decision the reviewer enforces is the same one the living documentation records.
Every change, checked across 13 lenses
The PR reviewer applies the same lenses a senior would. They run from core structure out to the optional deeper checks. Here are all thirteen.
Architecture
Real structure, layering, and whether boundaries hold. Module dependency direction, cycles, and ownership.
Migration
Coupling and dependency boundaries during a move. Shared or global state, conversion scars, and platform lock-in.
Flow
End-to-end operations: triggers, decisions, side effects, and outcomes. What the system does, not just what classes exist.
Security
Authn and authz, injection, secret exposure, and unsafe input boundaries. Weak crypto, SSRF, path traversal, and sensitive-data handling.
Code quality
Complexity, duplication, dead code, weak names, and SRP violations. Leaky abstractions and anti-patterns.
Data model
Schemas, entities, relationships, keys, and invariants. Serialization, migrations, lifecycle, and nullability assumptions.
Domain logic
Implicit product rules, invariants, permissions, and edge-case policy. The behavior that depends on context a static scanner can't infer.
Error handling
Silent failures, broad catches, and fallbacks that hide real errors. Retry, timeout, and cancellation behavior, plus cleanup leaks.
Bug hunting
Dropped guards, boundary errors, truthiness traps, and contract drift between producer and consumer. Plus the silent failure paths that mask failure as success.
Performance
Hot paths, N+1 patterns, unbounded allocation, and sync latency. Cache correctness and large-data handling.
Concurrency
Async, task, and thread correctness. Races, lock ordering, and shared mutable state.
Testing
Load-bearing paths without tests, brittle tests, assertion-free tests, and over-mocking.
Operability
Configuration, secrets, logging, metrics, and health checks. The deployment touchpoints that decide a smooth rollout.
Built on a memory that never forgets
Every finding, fix, and decision your team makes is retained. Heedvane gets sharper the longer you use it. The memory is the advantage, not any single check.
Regression memory
Re-introduce a bug you fixed in March and Heedvane can recognize it, and link back to the original fix and the reasoning.
Decision memory
New code is checked against the architectural decisions your team already made. The patterns you agreed on stay enforced.
Per-org learning
Every dismissal with a reason makes it quieter and more aligned to your standards. The review fits your team better each week.
Proof-carrying findings
Where it can, Heedvane backs a finding with a reproducing test or counterexample, not just an opinion.
Autonomy you earn, not a switch you flip
Heedvane earns more responsibility with data, per category, on your own measured precision. You are always in control.
- 01
Shadow
Runs silently and builds an accuracy baseline on your code.
- 02
Advisory
Comments, never blocks. The launch default.
- 03
Gating
Promote a category to a merge gate once it proves out, always with an override.
- 04
Auto-fix
High-confidence mechanical fixes opened as one-click, reversible pull requests.
Silent on day one. Autonomous only where it has earned the right.
Every finding arrives ready to close
Fix it yourself, hand it to your agent, or let Heedvane open the pull request.
- 01
Fix it yourself
Concrete fix steps and the evidence behind every finding.
- 02
Hand it to your agent
Export any finding as a ready-to-run prompt for Claude Code, Cursor, or your agent.
- 03
Let Heedvane open the PR
Heedvane writes the fix and opens a pull request your team reviews like any other.
Turn every scan into audit-ready evidence
The same first pass that reviews your code also documents it. Heedvane analyzes each change for compliance risk and turns the result into the report your audit asks for.
Specialized compliance scans
Heedvane analyzes your code for the risks your obligations care about, from data handling to access control, on every change instead of once a year.
Audit documentation, generated
The scan output becomes exportable, audit-ready reports and evidence, so prep stops being a scramble to rebuild screenshots the week before.
A trail for the whole population
Every finding, decision, and remediation lands in an append-only, timestamped trail, mapped to the frameworks you report against. EU AI Act and GDPR today, with more on the way.
You stay in charge. Heedvane produces the evidence; a human signs off on what ships.
Heedvane works with the tools your team already uses
- GitHub
- GitLab
- Bitbucket
- Azure DevOps
- Claude Code
- Cursor
Your seniors get their week back
The first pass is handled before anyone opens the pull request. Your senior engineers stop triaging style and obvious bugs. They spend their review time on the calls that actually need a human. Review stops being the thing that eats the week.
See the first pass on your own code
See the first pass run on your own pull requests. Book a demo, or create an account and we will contact you to arrange onboarding.