AI code review

AI code review from a panel, not one model.

Seat models from different labs, hand them your code or a GitHub pull request, and get back one list of findings ranked by severity. See where they agree, where they split, and what to fix first.

The Apex Directive discussion screen: a queue of issues ranked by severity, reviewers from different labs discussing the top one, and the merged recommendation.
Seat any mix of
  • Claude
  • GPT
  • Gemini
  • DeepSeek
  • Llama
  • Grok
  • Qwen
  • Kimi
Watch

See a code review in 27 seconds.

How it works

From pull request to a fix list in four steps.

1

Pick the code

Attach files, paste a diff, or pick a pull request straight from GitHub. Choose the code review type.

2

Discover

Every seat reads the code in parallel, each through its own lens, and returns findings rather than an essay.

3

Discuss

Open any finding and every seat weighs in on that one thing, including the models that never flagged it. Dismiss what does not apply.

4

Finalize

What survives becomes one markdown document: one recommendation per issue, ranked, with action items.

Why a panel

One model has blind spots. A panel covers them.

Models from different labs are trained differently and miss different things. Apex Directive does the sorting, so you read one list instead of diffing three replies.

Findings, not essays

Duplicates are merged into one list ranked by severity, with who flagged each issue and where they disagree.

Different labs, different lenses

Each seat is a model from a different company, given its own job. Where they agree, you can trust it. Where they split, you'll see it.

Pull requests from GitHub

Connect GitHub and pick a pull request instead of downloading and attaching files. The code follows the same path as any file you attach.

In your terminal and CI

The apex CLI runs the same panel on your own keys, and --ci fails a build when a finding crosses the severity you set.

Your table, your call

Seat two to five models from Anthropic, OpenAI, Google, DeepSeek, Meta, Alibaba, xAI and Moonshot, in any mix, and swap them per review.

Your work stays yours

We never store the files you submit and nothing is used for training. We keep what a review found, so History has it. Read how.

What you get

A review that ends in a fix list, not a pile of opinions.

  • One voice. A single recommendation per issue, with the discussion's conclusions folded in.
  • Ranked and actionable. Critical first, each with concrete steps you can act on.
  • Ready to paste. Download it as markdown for a doc, a ticket or a PR.
  • Saved to History. Come back to the findings later, from any device.

Bring your next review to the table.

Seven days on our keys with 250,000 credits. No card, so there is nothing to cancel.