Free during early access

diff in, noise out. the status quo.

Your AI code reviewer
doesn't know
your codebase.

hald builds a knowledge graph from your git history — ownership, coupling, risk. So reviews catch what matters and skip what doesn't.

Start freeSee how it works

The problem

Other tools see the diff.
hald sees the codebase.

Every AI reviewer feeds a raw diff to an LLM and prays. You get style nitpicks, false positives, and generic suggestions your team learns to ignore. hald indexes your git history first.

Ownership intelligence

Who built this? Who should review it? Mapped from git history, not manual CODEOWNERS. Expertise scores, knowledge silos, bus factor — all automatic.

Context-aware review

Deliberate patterns aren't flagged. The module expert gets lighter review. High-risk areas get extra scrutiny. Your team's knowledge becomes the filter.

Signal, not noise

Blast radius. Coupling detection. Bus factor alerts. Every PR gets a risk score grounded in your codebase's actual topology — not vibes.

git history is the most
underused dataset in software.

What it actually looks like

Your PRs, reviewed with memory.

hald-aibot

I found 2 issues in this pull request.

[CRITICAL] Unchecked null from getUserSession() — throws when session expires

src/api/auth.ts:47

Suggestion: Add null check before accessing session properties

[HIGH] SQL query concatenates user input without parameterization

src/db/queries.ts:23

Suggestion: Use parameterized query with prepared statements
hald — your codebase, held.
hald-aibot

Here's what I know about the files you changed.

Suggested reviewers

  • @sarah — 72% of commits in auth module
  • @marcus — 58% of commits in db layer
  • @chen — 31% across both modules

Blast radius

  • auth.ts co-changes with session.ts (14×)
  • queries.ts co-changes with user.ts (9×)

Bus factor warning

  • auth.ts — only @sarah has touched this file

Risk: HIGH (score: 0.82)

hald — your codebase, held.

Get started

Three steps. Zero config.

1

Install

One click. No config files, no CI changes, no tokens to manage.

2

Index

hald reads your git history and builds a knowledge graph. Minutes, not hours.

3

Review

Every PR: context-aware findings, risk score, suggested reviewers. Automatically.

Questions

You're probably wondering.

How is this different from CodeRabbit, Copilot, etc.?
They read diffs. We read your codebase's entire history. The knowledge graph means fewer, sharper findings your team actually acts on — not style nitpicks you learn to ignore.
Won't this add more noise to my PRs?
The opposite. The knowledge graph is a noise filter. If a PR is clean, hald says so and stays quiet. We optimize for signal, not volume.
Is my source code safe?
hald processes diffs in memory. The knowledge graph stores structural metadata — ownership, coupling, risk — not your actual code.
Does it block merges?
Never. Comment + informational check run. Your team stays in full control.
What if I disagree with a finding?
Dismiss it. hald tracks acceptance rates and learns from your team's decisions. Reviews get sharper over time.
How long until I see value?
30 seconds to install. Minutes to index. Your next PR gets the full picture.

Your codebase already
has the answers.

Free during early access. One-click GitHub install.

Start free