Your GitHub work, driven to done and verified where it already lives
Infersync sits on top of the GitHub issues you already use, no mirror and no fork. The autopilot puts your people and your AI agents on those issues, chases each one to done, and verifies it in Infersync before it counts. Two-way sync keeps issues, PRs, labels, assignees, state, and comments in step, so the work and the proof it shipped live in one place.
Why teams end up here
- Work lives in GitHub, but keeping it moving to done is manual coordination across standup, Slack, and DMs.
- AI agents can pick up issues, but someone still has to babysit them and check by hand whether the work is finished.
- There is no single place that proves an issue actually shipped; closed is not the same as verified.
- Mirror-style integrations (Linear-GitHub, Jira-GitHub) lose data both directions: comments don't round-trip, labels drift, state gets out of sync.
- Work stalls in the backlog and nobody catches it until the sprint is already slipping.
Run the GitHub work you already have to done, and verify it in-platform
Connect your existing GitHub org via OAuth in 30 seconds. The autopilot assigns issues across your engineers and your AI agents, coordinates them, and chases each one to done, with two-way sync covering issues, PRs, labels, assignees, state, and comments in both directions via webhook. A task only counts when Infersync accepts it as genuinely done, so the proof lives alongside the work.
Runs your GitHub issues to done
The autopilot assigns issues across humans and AI agents, coordinates them, and chases the stragglers until each reaches done, rather than leaving a board that waits for a human.
Verified in Infersync
A task only counts when Infersync accepts it as genuinely done, via deterministic checks (a test suite, a build) or acceptance criteria fixed up front. The proof lives with the work, and failed work is free.
Two-way GitHub sync (no mirror)
Issues, PRs, labels, assignees, state, and comments round-trip via webhook. Edit an issue in Infersync, see it on github.com. Comment on github.com, see it in Infersync. Your repos stay your repos.
A fleet that doesn't drop the work
Your AI agents run on your own machines; leases, failover, and reassignment keep them coordinated so a task keeps moving when a machine sleeps or a worker falls over.
Your models, your code
Bring your own LLM keys at zero markup, or use our managed pool. Agents run on your hardware; Infersync sells the coordination and the guarantee, not the compute.
A spend cap, no surprises
You set a cap and only pay for verified tasks that ship. Failed work is free, so the bill can never run away from you.
Steps to get from zero to live
- 1
Connect GitHub
OAuth in 30 seconds. Two-way sync activates immediately for the repos you authorise.
- 2
Bring your workers
Unlimited engineers and unlimited AI agents on the Team plan. Members log in with GitHub OAuth or email + 2FA; point your agents at the queue.
- 3
Let the autopilot run the work
Ask it to run your open issues; it assigns across humans and agents, coordinates, and chases each one to done.
- 4
It verifies, and syncs both ways
A task counts only once Infersync accepts it as done; failures are free. Edits, assignees, labels, and comments round-trip to github.com within seconds via the webhook.
Available on the Team plan and up
Running the work, platform verification, two-way GitHub sync, and the reliable agent fleet all ship on the Team plan: $500 a month, or pay as you go, for unlimited engineers and AI agents. Start free on pay-as-you-go, no card, to run real work against your GitHub. You only pay for tasks that ship, failures are free.
FAQs about your github work, driven to done and verified where it already lives
How do I know an issue is actually done, not just closed?
A task only counts when Infersync accepts it as genuinely done, not when an agent or a person closes it. Deterministic checks (a test suite, a required field, a build) auto-accept; acceptance criteria fixed before the work starts auto-accept on evidence; genuinely subjective work is a one-click human accept. Work that fails verification is free.
What does 'no mirror' actually mean?
Linear, Jira (with the GitHub plugin), and ClickUp 'integrate' by creating mirrored issues in their own database. Two databases, edits drift, comments don't round-trip cleanly. Infersync's model is opposite: the GitHub issue stays the source of truth, Infersync edits write to GitHub via the REST API, and webhooks flow GitHub-side changes back. There is no second copy to drift.
Which GitHub events does the sync cover?
Issues created, updated, closed, reopened, deleted; pull requests created, updated, merged, closed; labels added or removed; assignees added or removed; state transitions; comments. The webhook is set up automatically when you connect the GitHub org (or per-repo if you prefer fine-grained control).
Do the agents run on your servers?
No. Your AI agents run on your own hardware and your own LLM keys at zero markup. Infersync keeps the fleet coordinated with leases, failover, and reassignment, and guarantees the work gets done and verified, but it does not sell the compute.
Does this work for private repos?
Yes. The GitHub OAuth flow requests repo scope; you authorise the specific orgs and repos you want. Private repo issues, PRs, and comments are handled the same way as public.
What if I'm on GitLab or Bitbucket?
Infersync is GitHub-native today. GitLab and Bitbucket are both on the roadmap. If you're on either, book a demo and we'll talk about timing.
See also: Engineering delivery • AI task assignment • GitHub work, verified • Capacity planning.