Autonomous Feature Delivery
Submit a feature request. An AI agent builds it, tests it, and deploys it — no engineer in the loop.
A floating widget on any web app lets authorized users submit feature requests, bug reports, and improvements in under 30 seconds — without leaving their current context.
A Claude Code agent picks up approved requests, clones the repo, opens a feature branch, implements the change, writes tests, merges, and deploys — autonomously, 24/7.
A live dashboard shows all patches across all your projects — filterable by status, priority, and project. Color-coded statuses give instant visibility without a standup.
Email notifications keep submitters informed at every milestone. When the agent has a question, you get a direct link to answer — then it resumes automatically.
The Patch LoopIf the agent needs input, it emails the submitter → they answer in-widget → agent resumes. No engineer needed.
Traditional pipelines take 2–6 weeks. Patch: idea → approve → agent ships → deployed, often same day.
Patch handles the long tail — small UX improvements, copy changes, minor features. Engineers stay focused on hard problems.
No SDK. No npm package. One <script> tag and a project slug. Works on any web app regardless of stack.
Every patch has a complete audit trail: who requested it, when the agent picked it up, the PR URL, and the deployment timestamp.
Identifies friction daily but waits 2 sprints for a fix. With Patch, she submits the idea and it's deployed — often before the next standup.
Runs a 3-person eng team and can't afford developers fielding small feature requests. Patch acts as a zero-cost extra engineer.
Catches UX gaps in real-time demos. Wants to fix it now, not in 3 weeks. Patch gives her the ability to act on insight immediately.
Initially wary of autonomous deployments. Becomes the biggest champion when Patch handles repetitive, low-risk tickets.
| Tool | Collects Requests | AI Implementation | Auto-Deploy | No Eng Required | Widget Embed | Audit Trail |
|---|---|---|---|---|---|---|
| Patch |
✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Canny / UserVoice | ✓ | — | — | — | ✓ | Partial |
| GitHub Copilot | — | ✓ | — | — | — | Partial |
| Linear / Jira | ✓ | — | — | — | Partial | ✓ |
| Devin / SWE-agent | — | ✓ | Partial | — | — | Partial |
Nobody else connects the request → agent → deploy loop end-to-end with zero human engineering overhead.
Feedback tools (Canny, UserVoice) stop at collecting requests — no implementation.
AI coding tools (Copilot, Cursor) require an engineer in the loop.
PM tools (Linear, Jira) manage sprints but don't ship code.
Patch connects the request → agent → deploy loop end-to-end.
We're looking for AI-forward teams who want to move fast.