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Your AI assistant forgets. CrossCut remembers.

CrossCut turns code review findings into lessons your team approves, and hands them to Claude Code, Cursor and other assistants before they write code.

Developer task

Add an endpoint that receives a callback URL.

Context CrossCut adds

[RELEVANT LESSONS — do not repeat these mistakes]1. [a41f09c2] (area: api.ts) When building URLs from input data, check the protocol first: only http and https.2. [7be2d310] (area: panel-config) Every new Vite proxy route needs its location block in nginx.conf.[END LESSONS]
Illustrative example. Sample block. It carries the approved lessons closest to the task, within a token budget.

What is already measured

  • 1.00

    recall and precision for the deterministic gate, on a corpus of 34 files. On a live corpus of 300 cases, the 95% Wilson lower bound is 0.975.

  • 355

    approved lessons. The team that builds CrossCut uses it itself, as of October 26, 2026.

  • Not measured

    a reduction in repeated mistakes: that is not measured yet.

See all the evidence

The assistant forgets

Each session starts from scratch, so the same mistake gets written again. Review finds it once more, but only after the code exists.

When each tool acts
Before writingAfter it is written
Human reviewDoes not actFinds the mistake
PR botsDoes not actComment on the mistake
SonarQubeDoes not actFlags the mistake
CrossCutInjects the lessonCaptures the finding

From finding to certified rule

One example mistake goes through the five stages. Pick one to see what it produces.

Capture

The finding comes in from where code is already reviewed.

  • GitHub App: inline comments and review summaries from bot accounts, CodeRabbit included.
  • SonarCloud by webhook and connector, SARIF, and reviews captured from the assistant.
  • Before leaving the machine, the client redacts secrets and paths.

Finding

The URL is built from input data without checking the protocol.

Source
PR bot comment
File
src/api.ts
Status
Sanitized

Illustrative example

Distillation

A model turns the finding into a structured lesson.

  • A worker picks up each finding and distills it with DeepSeek.
  • The lesson stays a draft and is never approved on its own.
  • The project lead can choose not to distill.

Lesson Draft

What happened
A request was built from a URL that came from the user.
Cause
The protocol was not checked before using it.
Fix
Accept only http and https, and encode special characters.
Pattern
new URL(input) without checking url.protocol

Illustrative example

Curation

A person on the team decides what gets in.

  • Approve, edit or discard from the inbox, with keyboard shortcuts.
  • Lessons not reviewed within 90 days expire (reversible).
  • If the text carries instructions aimed at the model, approval is rejected.

Lesson

Accept only http and https, and encode special characters.

ApproveEditDiscard

draft, approved, discarded or expired. Today: draft.

Illustrative example

Injection

The lesson reaches the assistant before it generates code.

  • Only approved lessons take part: the 3 closest, above a similarity threshold.
  • Channels: MCP server, Claude Code plugin, Grok, Cursor and the CLI.
  • Every injection is logged.
[RELEVANT LESSONS — do not repeat these mistakes]1. [a41f09c2] (area: api.ts) When building URLs from input data, check the protocol first: only http and https.2. [7be2d310] (area: panel-config) Every new Vite proxy route needs its location block in nginx.conf.[END LESSONS]

Illustrative example

Certified rules

What can be mechanized becomes a rule that runs on its own.

  • A semgrep, lint or test rule is certified with positive and negative cases.
  • Only certified rules block; the rest inform or run in shadow.
  • It runs in pre-commit, in CI and in the plugin gate.

Rule url-without-protocol-check

Certified: blocks

  • Positive case: detects new URL(input) with no protocol check.
  • Negative case: lets through code that checks http and https.

It runs in pre-commit, in CI and in the plugin gate.

Illustrative example

What we measured, and what we did not

We do not promise fewer repeated mistakes: that is not measured yet. The corpora of each layer are not comparable with each other.

The benchmark is versioned in the repository. Two layers performed well on small corpora, one is weak, and the test with an agent was inconclusive.

LayerWhat was measuredResultReading
Deterministic gate34 files: 17 with a mistake and 17 cleanRecall 1.00, precision 1.00 and 0.00 false denialsOn a live corpus of 300 cases, the 95% Wilson lower bound is 0.975.Good on this corpus
Finding captureFindings collected from the sourcesRecall 1.00 and precision 1.00Good on this corpus
Lesson retrievalWhether the right lesson lands in the top 3Precision@k 0.33 on 8 prompts. Recall@3 of 0.33 with 300 lessons and 0.24 with 1,000The weakest layer
Test with an agent120 runs with an assistant, with and without CrossCut0.333 without CrossCut and 0.333 with CrossCutInconclusive

Today CrossCut is used by the team that builds it: 355 approved lessons and 832 drafts as of October 26, 2026.

“Mistakes avoided” in the panel is an estimate: injections minus recurrences. It does not measure whether the assistant used the lesson.

Integrations that exist today

What is live is called live. What only has a sample configuration is called that too.

Findings coming in

  • GitHub App Live

    Inline comments and review summaries from bot accounts.

  • PR review bots Live

    Generic: CodeRabbit comes in like any other bot.

  • SonarCloud Live

    By webhook and by project connector, with an encrypted token.

  • SARIF Live

    Ingestion through the API.

  • Review from the assistant Live

    With the MCP tool capture_findings or a hook.

Assistants that receive lessons

  • Claude Code Plugin

    A hook on every prompt and a gate on Write and Edit.

  • Grok Plugin and rules

    Lessons and rules inside the assistant.

  • OpenCode Plugin

    With feature parity.

  • Cursor Rules and hooks

    Installed with one command.

Unverified or unpublished

  • Codex, Gemini CLI and Continue Example

    Sample MCP configuration only; not verified in production.

  • GitHub Action crosscut-gate Unpublished

    It exists, but it is not published yet.

Privacy and control

What leaves your machine, what is stored and who decides. No promises we cannot keep.

Read the privacy policy
  • Every project is a silo

    Lessons from one project are not mixed with another’s. Only projects that turn it on take part in training: it is opt-in, revocable and audited.

  • You choose whether to distill

    With DeepSeek, already sanitized findings go to that provider. With the “none” option, nothing leaves.

  • Your prompts are not sent to third parties to find lessons

    Embeddings are computed on our own server; that text does not go to third parties. Prompts are kept for 90 days by default, configurable per project.

  • Nothing approves itself

    Every lesson goes through a person. Batch quarantine is reversible and deletes nothing.

  • Your data, in plain view

    JSON export, project deletion, user anonymization and a downloadable audit. The governance sheet carries a SHA-256 seal.

What is not there yet

  • The database is not encrypted at rest. Only integration tokens are encrypted, with AES-256-GCM. Traffic is encrypted in transit.
  • SOC 2 is on the roadmap; we do not have it.
  • The legal texts are drafts pending legal review.

Who receives data

  • DeepSeek: distillation, if the project chooses it.
  • Contabo: hosting for the server and the database.
  • Cloudflare: traffic, DNS and encrypted backups.
  • Resend: email with the access code.
  • GitHub and Kaggle: only in projects that gave consent.

Plans

Prices and limits are decided at launch. Today you can request early access.

Community

To try CrossCut with a small team before you decide.

Price at launch

  • Capture from the GitHub App, PR bots, SonarCloud and SARIF
  • Distillation with DeepSeek, or none if you prefer
  • Curation inbox with keyboard shortcuts
  • Injection through the MCP server and assistant plugins
  • Certified rules in pre-commit and CI
Early access: opening soon

Team

Main plan

For teams that code with assistants every day.

Price at launch

  • Everything in Community
  • Optional double approval for rules and batch quarantine
  • Recurrence, funnel and log metrics
  • Per-person API keys with rotation, revocation and expiry
  • Downloadable audit in CSV and JSONL
  • Monthly spend cap per project, with an alert at 80%
Early access: opening soon

Enterprise

For organizations with governance, provider or custom deployment requirements.

Price at launch

  • Everything in Team
  • Distillation provider chosen per project
  • Configurable retention, JSON export and project deletion
  • Governance sheet with a SHA-256 seal
  • Custom deployment and requirements: to be discussed
  • SOC 2: on the roadmap, not obtained; to be discussed
Talk to the team

Frequently asked questions

Is CrossCut a code review tool?

No. Review stays yours: human, with PR bots or with SonarQube. CrossCut takes what that review found and hands it to the assistant before it generates new code. It is not an IDE and does not replace the assistant.

Does my code leave my network?

With DeepSeek distillation, already sanitized findings leave: the client redacts secrets and paths, and the server sanitizes again, emails included. With the “none” provider nothing leaves. Prompts are turned into embeddings on our server. The providers are listed in the privacy policy.

Does it reduce repeated mistakes?

We cannot claim that yet. The deterministic gate did very well on its corpus, but the test with an agent (120 runs) gave 0.333 with and without CrossCut, with no conclusion. The detail is in the evidence section.

Who curates the lessons?

Any project member can approve, edit or discard. The lead manages members, providers, retention and integrations, and can require double approval for rules.

What does “avoided (estimated)” mean?

It is an estimate: injections minus recurrences. It does not prove the assistant used the lesson. “Injected” only means it was in a run’s block.

Which assistants does it work with?

Claude Code, Grok and OpenCode have a plugin; Cursor, rules and hooks. For Codex, Gemini CLI and Continue there are sample MCP configurations, not verified in production.

What happens when the spend cap is reached?

Each project has a monthly cap in USD. At 80% an alert goes up, and at 100% retrieval falls back to lexical search.

How much does it cost?

Prices are decided at launch. Meanwhile you can request early access.

Can I sign up and start today?

There is no automatic sign-up yet. Early access works by request: a person on the team reviews each one, creates the project and invites the lead from the dashboard.

Don’t let the next mistake repeat

We will open early access soon. For now we are not taking requests.

Early access: opening soon