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aiorch
Parallel AI agents that ship reviewed pull requests
Most coding tools hand you a diff. aiorch hands you a reviewed PR. It decomposes a task across parallel agents, auto-routes each to the best model (Claude, GPT-5, Kimi, Codex, Ollama — your keys), and runs three review rounds before opening the PR. Cross-provider routing first-party tools can't match. Runs in your Docker. Code never leaves the container. 0% token markup. Battle-tested on a 300k-line Rust telecom platform — multi-day refactors done overnight.
Hey everyone,
Necip here, the founder.
I built aiorch because I kept getting PRs that "AI wrote" but nobody had reviewed. Single-agent tools hand you a diff and the review burden stays with you.
aiorch makes the agents review each other before you ever see the diff. Three layers:
- An in-loop reviewer that critiques each coder and demands revisions until the work passes spec
- An independent auditor with no shared context (adversarial, not confirmatory)
- Integration tests across merged branches — no PR opens unless everything passes
The harder piece to build was cross-brand routing. Claude Code only runs Claude. Codex only runs OpenAI. That gap won't close — it's a commercial conflict, not a feature one. aiorch decomposes your task and routes each subtask to whichever model is best for the job: Claude, GPT-5, Kimi, Codex, or local Ollama. Mix them in a single run with your own keys.
Everything runs in your Docker container. Your code never leaves. Zero telemetry, 0% token markup — you pay providers at list price.
I dogfooded this hard while building TravelCalls — a 300k+ line autonomous Rust voice-agent stack for telecom. Multi-day refactors finished overnight as reviewed PRs. That pressure shaped the product.
5 minutes from `docker pull` to your first orchestrated session.
Two things I'd love to hear from you:
- What kind of work do you currently *not* trust AI agents with because of the review burden?
- If you've tried Claude Code or Codex and bounced — what was the trigger?
Happy to dig into anything technical.
About aiorch on Product Hunt
“Parallel AI agents that ship reviewed pull requests”
aiorch was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #159 on the daily leaderboard. Most coding tools hand you a diff. aiorch hands you a reviewed PR. It decomposes a task across parallel agents, auto-routes each to the best model (Claude, GPT-5, Kimi, Codex, Ollama — your keys), and runs three review rounds before opening the PR. Cross-provider routing first-party tools can't match. Runs in your Docker. Code never leaves the container. 0% token markup. Battle-tested on a 300k-line Rust telecom platform — multi-day refactors done overnight.
On the analytics side, aiorch competes within Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how aiorch performed against the three products that launched closest to it on the same day.
Who hunted aiorch?
aiorch was hunted by Necip Reis. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of aiorch including community comment highlights and product details, visit the product overview.
Necip Reis