Ship code, not tickets.
Assign a GitHub issue or Jira ticket — get a production-ready PR. Autonomous AI that reads your codebase, plans changes, implements, and self-reviews, then keeps the code healthy after it ships.
How it works
Four steps, and the last one never ends.
Sign up
Create an account, connect GitHub and Jira. Takes 30 seconds.
Create an issue
Write a GitHub issue or Jira ticket. Assign it to Coderhelm or add the label.
Review the PR
Coderhelm opens a PR, runs CI, and marks it ready. Request changes — it iterates.
It keeps going
After merge it watches the deploy, turns alerts into fixes and keeps its PRs current. Maintenance, not a handoff.
Under the Hood
A team of agents,
not a single prompt.
Every issue triggers an orchestrated state machine. Nine specialized agents pass structured state from stage to stage — with self-healing loops and automatic retries built into the fabric.
Triage
Classifies bug vs feature vs refactor. Scores priority and complexity.
Resolve
Fetches external context — Notion docs, Figma designs, Sentry errors — via MCP tools.
Plan
Reads repo conventions and produces a step-by-step task list with file paths.
Validate
Verifies files exist, imports resolve, and scope matches the issue.
Implement
Agentic coding loop — reads files, writes code, runs commands across your repo.
Test
Runs CI. If tests fail, reads logs and auto-pushes fixes — up to 3 healing attempts.
Review
Self-reviews like a senior engineer. Loops back to Implement up to 3 times if needed.
Security
OWASP audit for injection, XSS, SSRF, and secrets. Auto-remediates violations.
Ship
Formats the PR in your team’s voice, adds test evidence, and marks ready for review.
Self-correcting review loop
When the Review Agent finds issues — logic bugs, missing edge cases, naming problems — it sends structured feedback back to Implementation. The code gets fixed and re-submitted automatically. Up to 3 loops. The result: cleaner code than most human first-pass PRs.
Agent Memory
A knowledge graph
that learns your codebase.
Every run builds a living knowledge graph of your repository. Patterns, mistakes, conventions, architecture decisions — all connected, weighted, and retrieved exactly when the agent needs them.
Learns repo structure, conventions, test runner
Knows libraries, pitfalls, preferred patterns
Domain expert. Catches bugs humans miss
How the memory engine works
Knowledge Graph
Memories are connected by typed, weighted edges. The agent traverses the graph to find related context across runs.
Semantic Search
Vector similarity search finds relevant past learnings even when the wording is different. Understands intent, not just keywords.
Contradiction Detection
When new information conflicts with existing beliefs, the engine flags it. Old knowledge is superseded, not silently overwritten.
Salience Decay
Old, irrelevant memories naturally fade. Frequently accessed knowledge stays strong. The graph stays lean and useful.
Anti-Pattern Learning
When something breaks CI or fails review, it gets stored as an anti-pattern. The agent actively avoids repeating it.
Belief Propagation
When a fact changes, related beliefs are flagged for re-evaluation. Knowledge stays consistent across the entire graph.
Memory Tiers
Working, episodic, semantic, procedural. Different memory types are stored and retrieved with purpose-built strategies.
Team Isolation
Each team’s memory is cryptographically isolated. No cross-contamination. Your code patterns stay yours.
Intake
Works where you work
Native GitHub and Jira apps. Assign an issue to Coderhelm or add a label — a PR appears automatically. Comments on PRs with live progress. Reads your feedback, pushes fixes.
- Assign issues → get PRs
- Live PR progress
- Self-healing CI
- Native Forge app
- Label + assign = PR
- Project sync
AI Plans
Talk to your codebase.
Ship a plan in seconds.
Describe what you want to build. Coderhelm's AI searches your Notion docs, reads your Figma designs, and generates an executable plan — streamed to you in real-time, token by token.
The user wants GTM added to two properties. They mentioned a GTM ID in Notion — I should search for it before generating the plan...
Found "Analytics Config" — GTM-XXXX47F
Scanned layout files — no existing GTM snippet
I found your GTM ID (GTM-XXXX47F) in the Analytics Config page on Notion. Neither repo has GTM installed yet.
Here's a 3-task plan:
Real-time streaming
See the AI think and type, token by token. No loading spinners — just answers appearing as they form.
Searches your tools
Connects to Notion, Figma, Linear, Sentry and more via MCP. Pulls in IDs, specs, and context automatically.
Live plan preview
Tasks appear in the sidebar as they stream in. Review and refine before any code is written.
One-click execute
Approve the plan and Coderhelm opens PRs for each task — in order, with full specs and tests.
Review
A reviewer on every PR.
Not just the ones it wrote.
Add a label to any pull request and Coderhelm reviews it like a senior engineer who knows your codebase. It reads the code around the change, comments on the exact lines, and keeps reviewing as you push.
- Reads callers, contracts and tests in your repo, not just the diff
- Comments on the exact lines, with suggested fixes you can apply in one click
- Scores risk by how much of the codebase a change reaches, and shows why
- Re-reviews every push and resolves its own comments once they are fixed
- Answers questions in the PR: @coderhelm why is this unsafe? or @coderhelm re-review
The new start date reaches 3 callers. One still sends the old field, and the checkout test does not cover the new path.
high · startDate is sent as a string; the API expects an ISO date.
+ startDate: toIsoDate(form.startDate),
Merges only when it is safe
Optional auto merge, only for the exact commit it reviewed, after a person approves too and every CI check is green.
Runs the right CI
Adds the labels your CI listens for, such as which e2e tests to run or a staging deploy, based on what the PR actually changes. It uses the labels your repo documents, so new ones work with no setup.
Holds the line on tests
Optionally sends back any PR that adds or changes behavior without new or updated tests, and says what to test and where.
Code graph
Maps your repo into definitions and callers, so reviews (and the code Coderhelm writes) know exactly what a change touches.
Releases and health
Optionally tags releases after merges, batched on your schedule, and watches each deploy for new failures.
Learns from your team
Rate any review with a note. Future reviews on that repo follow your feedback, on top of your AGENTS.md and review rules.
Maintain
It doesn't hand off and walk away.
It stays on the code it ships.
Most AI tools stop at an open pull request. Coderhelm keeps working: it answers review comments, fixes the CI it broke, keeps its PRs current with main, checks every deploy for new failures, and turns production alerts into fixes your team reviews.
Answers review comments
Request changes or ask a question on its PR and it replies, pushes the fix and says what changed.
Fixes the CI it broke
When a check fails on its own PR, it reads the logs, fixes the cause and pushes again.
Keeps PRs current
Resolves merge conflicts with main before it works on feedback, so a PR doesn't go stale while it waits for review.
Watches every deploy
After merge, it waits for the deploy checks to finish and reports only failures that are new compared with before the merge. It never rolls back a shared branch on its own.
Turns alerts into fixes
Route your monitoring alerts to Coderhelm and the ones you choose become analyzed pull requests in the right repo. A person still approves every merge.
Tags releases
Optionally batches merged work into tagged releases on your schedule, with notes your team can read.
Check the facts
It looks before it guesses.
In your real systems, read only.
Connect your API, your logs and your database. While Coderhelm plans, writes code and reviews, it checks what the running system really has instead of guessing: whether a field exists, what a setting is, what the service logged. Given a bug ticket, it looks up the records the ticket names and the errors in the logs before it plans a fix.
- Your GraphQL API, your CloudWatch logs and your PostgreSQL database
- Bug tickets come with evidence: the record, the error, the code that raised it
- Reviews confirm a field or table really exists before flagging it
- Setup takes minutes: paste one script into AWS CloudShell, no engineer needed
- Every lookup is recorded, and your team can follow them live
SELECT id, renews_on FROM memberships WHERE id = 4182
filter @message like /renewal/ | sort @timestamp desc
RenewalJob: skipped 214 rows, timezone not set
The record is stale in the database, so the screen is right. The renewal job skips rows with no timezone. Plan: fix the job, not the screen.
Read only, enforced in code at every step
Not a promise in a prompt. Each lock below stops a write on its own, so a change would have to get past all of them at once.
One read at a time
Each lookup is checked before it is sent: one SELECT, one GraphQL query or one log search. Anything that could change data is refused and never leaves Coderhelm.
Rolled back, every time
Database lookups run in a read only transaction that is always rolled back. The database must confirm it is read only before anything runs.
A user that can only read
Coderhelm signs in as a database user that cannot change any table. It is checked when you connect and again before it is used.
A role tied to your team
Access goes through a role you create in your AWS account. Coderhelm can only use it with your team's private ID, and it is never allowed to commit a change. Delete the role and access ends.
Hidden stays hidden
Fields and columns you hide are refused wherever they appear. Secrets, email addresses and card numbers are scrubbed from results, and only the log groups you choose can be searched.
Every lookup on the record
Each lookup is logged with who asked, what they asked and for which pull request. Follow it live, and switch any source off with one click.
Monitor
AWS Log Analyzer
Connect your AWS account in one click. Coderhelm scans your CloudWatch Logs every 6 hours, surfaces errors with severity and root cause, and turns every finding into an actionable plan.
- One-click CloudFormation setup — read-only, nothing else
- Zero logs stored — only error summaries leave your account
- Secrets auto-detected and stripped before analysis
- AI severity scoring with root-cause suggestions
- One click from finding → executable plan
OOMKilled in ecs-api-prod — container exceeded 512 MB limit
Connection refused on RDS pg-main:5432 — 28 occurrences in 1h
Lambda timeout on invoice-processor — 15s exceeded 3 times
Zero-config setup
One CloudFormation click deploys a read-only IAM role. No agents, no daemons, nothing to maintain.
Privacy first
Logs never leave your AWS account. Only aggregated error summaries are analyzed — secrets are stripped automatically.
AI recommendations
Every finding includes severity, root cause analysis, and a suggested fix — ready to become an executable plan.
Integrate
MCP Servers.
Your tools, connected.
Connect your tools so Coderhelm can pull context during planning and execution. Pull Figma designs, query Sentry errors, check Datadog metrics, or read Notion docs — all while building your PRs.
Development & Design
Monitoring & Analytics
Data & Communication
One-click setup
Enable any integration with an API key or OAuth token. No config files, no YAML.
28+ integrations
Design, monitoring, database, deployment, and more. New servers added every week.
Available everywhere
MCP servers are available during AI Plans, PR runs, and log analysis. Context flows automatically.
Encrypted credentials
All tokens encrypted at rest and tenant-isolated. Credentials never leave your organization boundary.
Security
Built for teams that don't compromise
on security.
Your code never leaves your control. Every run is fully isolated, every credential encrypted, every action auditable.
Isolated Execution
Every run executes in its own container. No shared state — one team cannot access another's data.
No Code Storage
Source code is read through the GitHub API on-demand. Never cloned to disk or stored on our servers.
Encrypted Everything
All credentials, tokens, and secrets are encrypted at rest. Team data is partitioned — cross-team access is architecturally impossible.
Open Source
Free and open source.
CoderHelm is fully open source. Self-host it, contribute, or run it as-is. Bring your own API keys and set your own token limits.
Everything included
- Public & private repos
- All passes (ticket, PR review, CI fix)
- PR reviewer with auto merge, CI labels & code graph
- AI plans & streaming chat
- CI self-healing & log analysis
- MCP server integrations
- Bring your own API keys
Self-host
Deploy to your own AWS account. Full control over your data, infrastructure, and costs. CDK included. Requires Jira connectors, auth, and more — launching soon.
Ready to ship faster?
Free and open source. Deploy in minutes with your own API keys.