Infersync engineering autopilot
The autopilot
for engineering teams.
Give it a goal. It plans the work, routes each task to the right human or AI agent by skill, workload, and real cost across your GitHub, then tracks whether it actually got done. One queue for the whole team, human and AI.
Run it on your real GitHub · set up in 15 minutes · or explore the product
GitHub native
Two-way issues and PRs. It ships where you already work.
Cost per task, up front
Hours by rate, per task. Not month-end archaeology.
One queue for everyone
Engineers and AI agents take work from the same plan.
Watch it plan
A goal in, a costed plan out.
Type what you want shipped. The autopilot breaks it into tasks, picks who does each one, and totals the price before anything runs.
01 what it does
Not a dashboard to read. An autopilot that runs the work.
Boards wait for you to drag cards. Analytics tell you what happened last month. This asks for a goal and hands you a plan with a price on it.
Plan
Give it a goal in plain English. It breaks the work into tasks across your repos, with estimates.
Autopilot command barAssign
It ranks every person, and every agent, by skill, who is actually free, and what their hour costs, then routes each task to the best fit.
Skill + availability + costRun
Approve it and it executes: assignees, labels, due dates, state, straight onto your issues and PRs. Every action lands in the audit log.
Two-way GitHub syncTrack
Follow each task through to done, with PR and issue state synced back from GitHub and the real cost from tracked time. Know whether the work actually got done, and what it took.
Outcome and real costAlso in the box
Time tracking with clock in / out and breaksLeave and availability that feed the rankerNative tasks for work outside GitHubTime reports and billing CSVsSlack notificationsAPI keys + outgoing webhooks
02 agents
Humans and AI agents, one team.
Agents take work from the same queue as your engineers. The autopilot assigns to whoever fits the task, human or not, and every agent task carries a cost like everyone else's.
Bring your own AI workforce · available now
Connect the agents you already use. Infersync is model and provider agnostic, it cares about what a worker can do and what it costs, not whose model runs underneath.
Over MCP
Point any MCP client at your workspace. Infersync exposes work items, assignment, and status as tools your agent can call.
Over the API
A workspace-scoped API key lets any agent read work and post results. Rate-limited, revocable, no seat required to connect.
On your own infra
Run agents locally or on your own servers. Infersync coordinates the work; the model and the machine stay yours.
First-party agents · rolling out Q3 2026
Coding agent
Writes code, tests, and PRs against your repos.
QA agent
Reviews PRs, runs tests, flags requirement gaps.
Design agent
Drafts UI specs and mockups from requirements.
Docs agent
Keeps technical docs in sync with shipping code.
Bring your own LLM keys. You pay Anthropic, OpenAI, or Google at their rates; we add no markup on tokens. First-party agents roll out in Q3 2026, early-access customers first.
03 performance
Route by what a worker actually does, not by job title.
Assignment shouldn't rest on titles or model names. Infersync ranks every worker by skill fit, who is actually free, and the real cost per task from tracked time, and skill proficiency shifts as work completes faster or slower than expected. The cheap, quick worker wins the small task; the expert wins the one that needs them.
| Worker | Best at | Median time | Avg cost | Skill match |
|---|---|---|---|---|
| Backend AgentMCP agent | API endpoints, migrations | 22 min | $0.34 | High |
| SarahEngineer | Schema and data changes | 68 min | $41 | High |
| Review AgentMCP agent | PR review, test gaps | 9 min | $0.11 | Medium |
| AhmedEngineer | Architecture decisions | 3.1 hr | $186 | High |
Illustrative figures, not customer data. Median time and cost come from your own tracked work once you connect.
04 github
Works with the workflow you already use.
Infersync connects to GitHub so your issues, pull requests, and engineering workflow stay the source of truth. It reads work in and writes decisions back, two ways. Nothing to migrate, no board to rebuild.
Infersync never reads your source code. It works with the metadata of your work, issues, PRs, labels, and state, not your files.
Synced two ways
- Issues and pull requests
- Labels, assignees, and state
- Comments and reviews
- Projects and boards
05 try it now
What did your repo cost to build?
Paste any public GitHub repo. We read its commit history and put a floor under what it cost in engineer time and money. No signup, no email.
It is a floor on purpose: planning, design, and debugging never show up in commits. The real number comes from tracking work as it happens, which is the part Infersync does.
06 versus
Boards track. Analytics report. This runs it.
| Jira / Linear | Jellyfish / LinearB | Infersync | |
|---|---|---|---|
| Assigns work by skill + cost | Manual | No | Automatic |
| Real cost per task | No | After the fact | Live |
| Humans and AI agents as one team | No | No | Native |
| Brings you the decision | No | No | Yes |
Head to head: vs Jiravs Linearvs Mondayvs ClickUpvs Asanavs Notion
07 where we are
Early, and honest about it.
We could put a wall of logos here. We don't have one yet, and inventing it would defeat the point of a product built on real numbers. Here is where we actually are.
The product is live, teams are onboarding, and you can walk through the demo workspace without signing up.
teams signed up since launch, through channels we pay nothing for. We talk to them daily.
spent on ads No ad budget, no SDR team. Every team found us through work we published.
founder Email hello@infersync.com and a human who wrote the code answers.
08 pricing
One product. One clear path.
Start with a 30-day pilot on your real work. Then run your team, up to 25 engineers and unlimited AI agents, on a flat monthly plan. Enterprise when you grow past that.
Billed monthly, cancel anytime.
Prove it on your real engineering work.
- The full product for 30 days
- Up to 25 engineers, unlimited AI agents
- AI Autopilot, human + AI routing, GitHub two-way sync
- Performance, outcomes, time and cost tracking
- Pilot onboarding, included
- Pilot analysis and report, included
- Dedicated founder support, included
One team running a hands-on 30-day pilot, with founder support.
The autopilot for your engineering team, ongoing.
- Up to 25 engineers, unlimited AI agents
- AI Autopilot: give a goal, it plans and routes the work
- AI task routing by skill, availability, and real cost
- One queue for humans and AI agents
- Two-way GitHub sync (issues, PRs, labels, state, comments)
- Performance and outcome tracking through to done
- Time and cost per task, for people and agents
- Connect your own agents over MCP or API, bring your own LLM keys
GitHub-native teams up to 25 engineers running humans and AI agents together.
Autopilot at org scale.
- Everything in Team, beyond 25 engineers
- Dedicated or single-tenant deployment
- SSO and SCIM (rolling out)
- Extended audit log retention
- Custom integrations
- Dedicated success engineer and SLA-backed support
- Procurement-friendly: MSA, DPA, security review on request
Teams beyond 25 engineers, and orgs with security and procurement needs.
14-day free trial on Team. No credit card. Trial workspaces get Team-tier features for the full 14 days. Tour the dashboard.
- Those are task managers. They store work. Infersync orchestrates work: it routes tasks to humans or agents based on skill, availability, and cost, then tells you what each task actually cost to deliver. We sit one layer below your task manager, not next to it.
Operator's note
One email a month. Receipts, not noise.
Product launches, agent rollouts, pricing changes ahead of time, and lessons from running hybrid human-AI teams. Two minutes to read, one click to leave.
Run a 30-day pilot on your real engineering work.
Connect GitHub, route work to your engineers and AI agents, and measure what actually shipped and what it cost. See your first plan this afternoon.
One engineering team · runs on your GitHub · set up in 15 minutes