Skip to main content

AI agents that do real engineering work.

Put AI on the bugs, upgrades and maintenance your team never gets to. It runs on your own infrastructure, nothing ships without your approval, and you can undo anything it does.

  • Runs on your infrastructure
  • Works with GitHub, Jira and Slack
  • Your code never leaves your network
One ticket, start to finish checkout team
  1. Mon 09:00 Picked up ticket #2841   duplicate confirmation emails started
  2. Mon 09:05 Reproduced the bug and wrote a test for it working
  3. Mon 11:38 Fixed it — 214 tests pass   3 files changed done
  4. Mon 11:39 Opened a pull request for review waiting
  5. Mon 14:02 You approved it approved
  6. Mon 14:32 Shipped, then watched for 30 minutes   no errors verified
The problem

Why AI pilots stall in engineering teams.

The work never actually lands.

A chat session ends and so does the work. Nothing was finished, nothing was tracked, and nobody can pick it up tomorrow.

Your security team says no.

And they are right to. Handing production access to something nobody can govern, audit or reverse is not a risk anyone should sign off.

It cannot reach your systems.

Your repositories, test databases and internal services are not on the public internet, and they are not getting a firewall exception.

NovaCore was built to solve those three first, and the AI part second.

What you get

Four things you can hold us to.

Work that gets finished

Assign a ticket, get a reviewed pull request with tests. It keeps going across days, waits for people without burning budget, and picks up exactly where it left off.

Nothing ships without you

Anything that touches production comes to you first — what it wants to do, why, what it affects, and how to undo it. One click to approve, one to reject.

Your code never leaves

Agents run on machines you own, inside your network. We never need access to your systems, your VPN, or an inbound firewall rule.

Proof, not promises

Watch any agent work, live. See what it changed, what it cost, and how often your team had to correct it — per team and per repository.

Staying in control

You approve anything that matters.

Every change that reaches production arrives as a plain-English summary. No dashboards to learn, no logs to read.

It tells you what it wants to do, why it thinks that, what it affects and how to undo it — then waits. In the browser, on the pull request, or in Slack. Whichever you already use.

If you approve it, it ships and then keeps watching. If anything looks wrong in the next half hour, it puts things back on its own.

Waiting for you needs approval

Ship the fix for duplicate confirmation emails

What it wants to do
Ship a fix for duplicate order confirmation emails. 3 files changed.
Why
Ticket #2841. It reproduced the bug, wrote a test for it, and all 214 tests pass.
What it affects
The checkout service, in production. No spending involved.
How to undo it
Roll back to the previous release. It will watch error rates for 30 minutes after and undo it automatically if anything looks wrong.
Approve Reject Ask a question See the work
How much rope

You decide how far it can go.

  1. Watch only It reports what it would do. Changes nothing.
  2. Suggest It writes up the fix and the reasoning for a human to act on.
  3. Draft it It does the work and opens a pull request, then stops.
  4. Ask me first It can ship — once you approve. Where most teams stay.
  5. Go ahead It ships inside limits you set, on work you nominated.

Set it per team, per repository, and per kind of work — tighter for anything near production, looser for a dependency bump.

Most teams start at ask me first for anything customer-facing and stay there. That is a perfectly good place to stay.

Fits your setup

Works with what you already use.

Where your work lives
GitHub GitLab Azure DevOps Jira Linear
Where your team talks
Slack Microsoft Teams Email
Which AI does the work
Claude Code Codex Cursor your own keys

Bring your own AI accounts and pay your own rates. When a better coding agent arrives — and one will — you switch it in settings rather than in a migration.

Getting started

Your first ticket, this week.

  1. 01

    Connect a repository

    Takes minutes. Read-only to begin with.

  2. 02

    It reads your codebase

    And proposes how to build, test and deploy it.

  3. 03

    You confirm what is production

    The one thing it is never allowed to decide alone.

  4. 04

    Assign it a ticket

    And watch the first one run.

See it run on your own code.

A working session rather than a slide deck. Bring a repository and a ticket you would otherwise assign to someone, and watch it go from the ticket to a pull request you approve.