Solutions / Developer

Give an agent the pager.
And the keys to fix it.

An agent that can only talk is a chatbot. One with tools, memory, and permission to act can hold a rotation, work a backlog, and ship. Apteva is open source, so you can read exactly how it does it.

01

An alert wakes a human who then reads logs for twenty minutes.

The page fires at 3am. Most of that twenty minutes is reconstruction: what deployed recently, has this fired before, what did we do last time. The actual fix is often the short part.

What Apteva does

The agent does the reconstruction before you are awake. It arrives at the incident with a correlated picture rather than handing you a notification and a dashboard link.

Where you stay in control

It proposes; you merge. Production changes sit behind whatever approval you already require.

How it runs

  1. Groups related alerts into one incident instead of paging separately for each symptom.
  2. Pulls the logs and metrics around the failure window and identifies what actually changed.
  3. Correlates against recent deploys, config changes, and past incidents with the same signature.
  4. Writes a diagnosis with the evidence attached, and drafts the fix or the rollback for review.
  5. Schedules its own follow-up check after any change, and keeps the incident open until the signal is genuinely clear.
02

The small fixes never reach the top of anyone's list.

The dependency bump, the flaky test, the stale config, the TODO from eight months ago. Each is twenty minutes, none is worth interrupting feature work, so the pile grows until something in it breaks.

What Apteva does

The agent works the long tail continuously in the background, at a pace that does not flood your review queue, opening each change separately so it can be judged on its own.

Where you stay in control

Every change is a reviewable diff. The agent never merges its own work unless you explicitly allow it.

How it runs

  1. Keeps a standing backlog of small changes, from your issues, TODOs, failing tests, and dependency alerts.
  2. Works one at a time in an isolated environment, running the tests before it proposes anything.
  3. Opens a focused change with the reasoning and the test result, rather than a large mixed pull request.
  4. Paces itself against how fast reviews clear, so the queue never becomes the bottleneck.
  5. Drops anything that cannot be verified, and says so, rather than shipping a change it could not test.
03

You want agents inside your own product, not another SaaS.

Hosted agent platforms put your data, your prompts, and your tool definitions behind someone else's API, priced per seat, with a roadmap you do not control.

What Apteva does

Apteva is the runtime, not the product. Build your own apps against the SDK, expose your own tools, run it on your own infrastructure, and choose the models. The whole thing is open source and readable.

Where you stay in control

No vendor sits between your agent and your data. Deployment is a decision you make, not a pricing tier.

How it runs

  1. Write apps in Go against the SDK: your own tools, HTTP routes, UI panels, background workers.
  2. Expose those tools over MCP so agents — yours or other people's — can call them.
  3. Run it on your laptop, your server, or your cloud. The same binary, with your data staying where you put it.
  4. Choose the models per agent, including local ones, and see exactly what each run costs.
  5. Fork it. The licence is MIT and the code is the documentation.

What changes

Fewer interrupts, a backlog that actually moves, and an agent runtime you can inspect, extend, and host yourself.

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