Machine-like watches every run of every agent it operates. When a run goes wrong, the agent stops before anything goes out. We find the cause, ship the fix, and tell you what changed.
You never operate an agent. Monitoring, holds, fixes, connection upkeep, and changes on request come with every workload. Operations is the product, not an add-on.
No ops fee. No setup fee. No credit card to try. Your 14-day trial starts when your agent goes live.
One workload starts at $297/month after the trial, operations included. Month-to-month. Cancel anytime.
Illustration: an operations console watching four agent workloads. Runs are counted as they finish. When a run meets something it has no rule for, it is held, fixed, and replayed, and each event is written to the ops readout.
Anything the agent doesn’t recognize is held, not guessed.
What broke, what we changed, and why. In plain English.
Building, running, and fixing the agent is on us.
AI agent maintenance is the ongoing work of keeping an agent correct in production: watching every run, holding anything uncertain, fixing what breaks, and updating the agent as your tools and process change. Machine-like includes it in every workload.
Illustration: over twelve weeks, the same four surprises hit two copies of an agent: an expired login, a vendor API change, a new CRM stage, and a model update. The operated agent holds each time and returns to standard after a fix. The unattended agent drops a step with each surprise and does not recover.
Most agents don’t fail on launch day. They fail in month three, when a login expires, an app changes its API, or a new kind of record shows up.
An agent nobody maintains degrades one surprise at a time, usually quietly. An operated agent meets the same surprises, holds the work instead of guessing, and comes back to standard with a note that explains the fix.
What you get: an agent that stays at the standard agreed at scoping, without anyone on your team running it.
Machine-like covers run monitoring, approval gates, holds on unknown input, fixes with receipts, connection upkeep, and changes on request for every agent it operates. None of it is billed separately.
Every scheduled and triggered run is checked. Late, missed, and failed runs are flagged automatically.
Work that needs your sign-off waits in the Terminal, Slack, or email with the draft attached. Nothing behind a gate moves until you say so.
When the agent meets an input or a case it has no rule for, it stops and holds the work until the rule exists.
We replay the run, find the step that broke, and ship the fix. Every step writes a record: inputs, outputs, timing, and what changed.
Expired logins and changed APIs are caught and repaired, and the work held in the meantime is re-run.
Your process changes. Tell us in Slack or the Terminal, and we update the agent. The next run uses the new version.
Start with one recurring job. Operations covers it from the first run, and every workload you add later gets the same watch.
When a Machine-like agent meets something it has no rule for, the run halts before anything is sent. Machine-like is alerted, replays the run with identical inputs, ships the fix, and sends you a note explaining what changed.
The failure: a lead follow-up agent meets a CRM stage, “Re-engaged,” that was added after launch. It has no rule for it.
Halt
Step 3 meets the new stage. Instead of guessing, the agent holds the run. Zero messages go out.
Alert
The hold notifies Machine-like with the run, its inputs, and the step that stopped. You don’t have to notice, triage, or forward anything.
Replay
We rerun the exact inputs in a sandbox where nothing sends, reproduce the failure, and see what the agent would have done next. The cause comes from the receipts, not a guess.
Patch
We add the missing rule, re-run the held step, and send you a short note: what broke, what we changed, and why.
The 14 drafts still wait at your approval gate. A fix never skips a gate you chose.
With an agent you build, or one you configure in an agent tool, someone on your team catches and repairs every failure. With Machine-like, the repair is part of the service: Machine-like detects the failure, fixes the cause, and replays the missed work.
| The failure | Agents you build | Agents you babysit | Machine-like |
|---|---|---|---|
| An expired loginA connected tool logs the agent out. | Runs fail quietly until someone notices. You reconnect and redeploy. | The tool emails an error. You reconnect and re-run. | We catch the failed call and hold the run. If only you can re-authorize, you get a one-click link. Then we replay what was missed. |
| A vendor changes its APIAn app updates and the old call stops working. | You read the changelog, debug, and ship a fix. | You wait for the vendor to update its connector. | We update the integration and re-run the held work. |
| A model update shifts behaviorSame instructions, different output. | You find out from a customer. | You re-tune the prompts and hope. | We review output quality against the standard agreed at scoping and correct the agent when it drifts. |
| An input it hasn’t seenA new field, stage, or format appears. | The agent guesses. You clean up after it. | It depends on the tool. Often it guesses, too. | The agent holds instead of guessing. We add the rule and re-run. |
| Your process changesNew pricing, a new owner, a new step. | You rewrite the workflow. | You reconfigure it and test it again. | Tell us in Slack or the Terminal. We update the agent. |
| A draft isn’t rightWrong tone, wrong fact, wrong person. | You edit the draft and patch the prompt. | You edit the draft. Next week, again. | Reject it at the gate with a note. We fix the cause, not just the draft. |
Comparisons describe common patterns, not a specific product.
Machine-like sends a weekly after-action report built from the run logs: what ran, what finished, what waited on you, what failed, and what changed. Every line traces back to a run receipt.
After-action report · Week of Nov 2
Northline Mechanical
Your CRM has a new stage, “Re-engaged.” The agent had no rule for it, so it held the run instead of guessing. We added one: re-engaged leads now get the nurture follow-up.
Nothing was sent during the hold. No action needed from you.
“Can the SEO report land Monday mornings instead?”
v1.4v1.5schedule: Mon 06:00 ET
Illustrative sample. Every run writes a receipt: inputs, outputs, timing, and what changed.
Machine-like commits to halting on unknown input, detecting every failed, late, or missed run, acknowledging alerts within 4 business hours, and sending a note for every change. The operations fee is $0, and workloads start at $297 per month.
Detection is on. Every run is checked at any hour.
You never build, configure, monitor, or debug an agent.
Price
$297per workload / month · operations included
No setup, integration, or platform fees. No credit card to try. Cancel anytime.
Customers
From founder-led teams who handed real work to Machine-like and stopped thinking about the machinery.
Our partners at Machine-like gave us a more responsive support operation without forcing a massive migration. The agents worked across our systems and kept me in the loop when something needed my attention.
We looked at a few vendors, including building the agents ourselves. Every option required technical resources that we couldn’t spare. I needed these tasks done, and the team at Machine-like just handled it.
Case study · fitDEGREE
Ticket classification, context lookup, responses, and record updates, with escalation for anything the agent shouldn’t handle alone.
Common questions
What we handle, what stays with you, and what happens when something goes wrong.
Sending, publishing, and record changes can sit behind approval gates you choose during scoping. If a bad output still gets through, we pause the workflow, trace it in the run log, fix the cause, and send you a note on what happened and what changed.
Detection is automated and always on. Every run is checked, and anything late, failed, or uncertain is held automatically, at any hour. Our team works the fix during business hours, Eastern time, and acknowledges every alert within 4 business hours.
Drift is when an agent’s output slowly stops matching what you agreed to, usually after a model update or a change in your data. We review output quality against the standard set at scoping and correct the agent when it moves. You can also flag a bad output at any approval gate.
Three things: approve work behind the gates you chose, authorize the tools the agent uses, and tell us when your process changes. You never build, configure, monitor, or debug the agent.
No. Operations is included in every workload, from $297 per month per workload. There are no setup, integration, or platform fees.
You authorize each tool through Composio, a managed connection layer, so your raw passwords and API keys never pass to the agent or to us. You can revoke a connection at any time.
Cancel anytime. We stop your agent’s runs. The work it did stays in your own tools, because that’s where the agent worked.
Automation tools are configured and kept running by you. When something breaks, it’s on you. With Machine-like, we build the agent, run it, and fix it. You judge the finished work.
Your agent, under watch
Machine-like builds, runs, and maintains each agent, and operations is included in every workload from $297 per month.
Bring one recurring job. We scope it, build the agent, and watch every run from the first one. Your 14-day free trial starts when the agent goes live.