AI agent maintenance in production
An agent works until something changes: an integration fails quietly on Saturday, a stale rule starts posting an invoice to the wrong account, and small errors pile up for weeks until someone on the board asks why the numbers don't add up. Maintenance is care for an agent in production, with a named engineer accountable for it: each month they read the logs, catch the edge cases, correct the rules and hand over a report before the board notices the problem. Quoted individually, a monthly contract, with regression monitoring, a fix SLA and Cost Per Query in the report; we only run systems with logs and an owner, because without a trace an agent cannot be run responsibly.
In short
- Billing
- Quoted individually, monthlyby the work, not the number of agents; full cost before signing
- Every month
- Logs, edge cases, fixes, a reportwe catch them before the board notices
- What the report shows
- Regression monitoring and Cost Per Querythe per-query cost, not just the model invoice
- Only for
- Systems with logs and an ownerwithout a trace an agent cannot be run responsibly
Problem
An agent works until something changes. An exception nobody planned for shows up. An integration fails quietly on a Saturday. A stale rule starts posting an invoice to the wrong account and nobody notices. Small errors pile up for weeks, until someone on the board asks why the numbers don't add up, or why the model bill went up.
Outcome
You get an agent that doesn't break quietly, and a monthly report you can show the board. A standing engineer-owner reads the logs, catches edge cases before they become outages, and corrects rules before they hit the numbers. The report also shows cost: what the agent used and Cost Per Query, so the model bill stays predictable, not a surprise. A monthly rhythm, not a fix after the outage. Priced individually, after the scan.
This is a month of maintaining an agent.
We don't wait for an outage. Every month we run the same cycle, and the green line is the boundary the system does not cross alone.
- 01
We read the logs and alerts
monitoring gathers what the agent did and where it behaved unusually
- 02
Edge-case analysis
we catch new exceptions and cases the rules don't cover yet
- 03
Correcting rules and boundaries
we fix prompts, rules and integrations before they become outages
- 04
Monthly work report
what the agent did, what it escalated and what we fixed, in plain language
Correction within bounds
a prompt, threshold or rule fixed without changing the production effect
Change with production impact
a new action or wider boundary waits for approval from a human on your side
We set the boundary beyond which a change needs approval in the maintenance contract. The system does not widen its own permissions.
Scope
- Monitoring and alerts: we know about a problem before your team reports it
- A bug-fix SLA by package, with an agreed scope of small changes
- A monthly edge-case review, with prompt and rule corrections
- Model lifecycle: when a provider retires a version, we re-pin the agent to its successor and run the eval suite before the cutoff, so behavior does not change silently
- A monthly agent work report: what it did, what it escalated, what we fixed
- Cost under control: Cost Per Query in the report, model selection per task, and hard filters that keep the model away from cases it doesn't need to touch
- Engineering hours for boundaries, escalation and integrations as the process changes
- One client's data kept separate from others, a dedicated VM on request
Data & compliance
One client's data kept separate from others, a dedicated VM on request, human oversight on production-impact actions, and monitoring in the spirit of Art. 72 of the EU AI Act: every action leaves an audit-ready trace.
Not for
- Agents built without logs or an owner: without a trace they can't be run responsibly
- Companies that won't allow monitoring of how the system behaves
- One-off advice without continuous responsibility for production
- A system we're not allowed to inspect or change
How much care does your agent need.
Maintenance
priced individually
What it covers
Hosting, monitoring and alerts, a fix SLA with a small-change pool, a monthly edge-case review, plus engineering hours for boundaries, escalation and integrations as the process grows.
What it costs
priced individually
ongoing oversight · Maintenance and oversight · monthly
The price follows the work, not the number of agents.
We price maintenance individually, after the free scan. You know the full cost before signing, with no hidden items.
What drives the price
- The number of systems and integrations under watch
- Process criticality and the required fix SLA
- The scope of changes and engineering hours per month
- Security, consent and audit requirements
Sources
- EU AI Act 2024/1689, Art. 72
- Article 72 obliges providers of high-risk systems to monitor after deployment. Maintenance delivers that rhythm and documentation regardless of the system's classification.
- Gartner, 2025
- Over 40% of agentic AI projects will be canceled by end of 2027, most often from escalating costs, unclear business value, or weak risk controls.
Free process scan
Start with a free process scan.
- 30 minutes with the engineer who would build it, not a salesperson.
- A review of the processes that cost you the most time and money.
- A written summary: what to automate, in what order, with cost ranges.
No sales deck and no obligations. If automation doesn't make sense, we'll write that too.
0 PLN
30 minutes · written takeaway within 2 business days
You leave with a plan, not a sales pitch.
- 30 minutes with the engineer who would build it, not a salesperson.
- A review of the processes that cost you the most time and money.
- A written summary: what to automate, in what order, with cost ranges.
No sales deck and no obligations. If automation doesn't make sense, we'll write that too.
Maintenance questions
Do you maintain an agent someone else built?
Only if it has logs and a technical owner. Without an action trace it can't be monitored or fixed responsibly. We start with a short audit that shows what's missing before it can be run.What exactly do you do each month?
We read the logs and alerts, analyse the edge cases and correct rules and boundaries before they turn into outages. At the end you get a report: what the agent did, what it escalated to a human and what we fixed. A rhythm, not a reaction after an outage.What does the monthly agent work report look like?
A few pages in plain language, not a console dump. It shows what the agent handled, where it stopped and handed a case to a human, and which corrections we made. You can show the document to the board or an auditor.What if the agent starts making mistakes between reviews?
Monitoring and alerts catch unusual behaviour early, so we usually know about a problem before your team reports it. Response time and the scope of urgent fixes are written into the SLA for your package, not decided ad hoc.How much does AI agent maintenance cost?
The price doesn't follow the number of agents, it follows the work: the number of systems, the criticality and the scope of change. So we price maintenance individually, and you know the full cost before signing. We scope it after the free scan.Do you track model cost, and can the bill blow up?
Yes. Cost Per Query is one of the metrics in the monthly report, alongside the agent's work and its escalations. We cut it where we can: we pick the model per task, and hard filters keep the model away from cases it doesn't need to touch. On request we set a monthly cost limit so the bill stays predictable.Is my data safe?
One client's data is kept separate from others, and a dedicated VM runs on request. Operations with production impact wait for human approval, and every action leaves a trace. Art. 72 of the EU AI Act places a formal post-deployment monitoring duty on providers of high-risk systems. Most automations and agents are not high-risk systems, but the same rhythm gives you an audit-ready trace regardless of classification.Can I cancel, and what's the notice period?
Yes. Maintenance is a monthly contract with a simple notice period written into the agreement, no multi-year lock-in. The logs, documentation and configuration are yours, so you can take the agent over yourself or hand it to another team.