The Mitari Platform

AI code review for data, analytics & ML teams

Catch silent failures across pull requests, repos, and local files. Mitari reviews data science, analytics, and ML code for leakage, evaluation mistakes, reproducibility bugs, and production risks — in GitHub, across repos, and through an API.

GitHub PR Reviews
Observability Graph
Auto-fix PRs
API
Product Pillars

One platform. Four surfaces.

From pull-request review to repo-wide observability, automated fix branches, and an API for local files — Mitari covers the full code-quality loop for data, analytics, and ML teams.

GitHub PR Reviews

Catch data and ML bugs before they merge.

  • GitHub Checks
  • Inline annotations
  • Diff vs existing split

Observability Graph

Map issue patterns across repos and files.

  • Repo-level visibility
  • File-level Fathom
  • Watchlist alerts

Auto-fix PRs

Turn selected findings into targeted fix branches.

  • Selected findings
  • Semantic checks
  • Fix-blocked safety

API

Review local SQL and Python files from scripts and CI.

  • Submit local files
  • Poll results
  • API keys · 100/hour
How Mitari works

From connect to clean in four steps

No infrastructure to run. Connect GitHub, upload, or POST a file.

Connect or upload

Install the GitHub App, or POST a file to the Mitari API.

Mitari reviews

Fathom inspects every changed file for leakage, eval mistakes, and reproducibility bugs.

See findings

Severity-ranked issues land in PR Checks, the Observability graph, and the Run Report.

Open fixes

Generate a verifier-safe fix PR for selected findings, or fetch results from the API.

Observability Graph

See issue patterns across repos and files

Mitari maps every reviewed file in your repo to a single graph — clustered by severity, ranked by Fathom score. Spot the riskiest modules at a glance, drill into a file, and rerun Fathom from the node itself.

  • Repo-level visibility
  • File-level Fathom runs
  • Severity trends
  • Watchlist email digests
Auto-fix PRs

Selected findings become targeted fix PRs

Pick the findings you want addressed, and Mitari opens a focused fix branch — bounded by semantic-drift checks, syntax verification, and a fix-blocked surface when the change isn't safe to apply.

API

Review local files from scripts and CI

POST a SQL or Python file to Mitari's REST API, poll for the result, and link straight to the Run Report. Authenticate with an API key generated from your account.

Submit a file POST
$ curl -X POST "https://mitari.ai/api/v1/reviews/files" \
  -H "Authorization: Bearer $MITARI_API_KEY" \
  -F "filename=query.sql" \
  -F "file=@query.sql"
Result JSON
{
  "status": "succeeded",
  "counts": {
    "critical": 2,
    "warnings": 1,
    "opportunities": 0
  },
  "run_url": "https://mitari.ai/app/runs/123"
}

Authenticated, rate-limited at 100 requests/hour, and integrated with the same Run Report your team already uses.
Sign up to use the API →

The Run Report

Actionable findings, clear severities,
and one-click PR resolution.

Every run produces a report card with critical issues, warnings, and opportunities — plus a button to launch Mitari's fix PR directly.

Mitari run report showing critical issues, warnings, opportunities, and the Launch Mitari Agent PR button

Start reviewing data and ML code today.

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