An integration nobody owns
The model works in a notebook and the ERP never hears about it. We build the backend and the integrations that carry the answer to where the work happens.
Read
Technology
The software around the model, built to last.
Architectures and software engineered to run in production, not just in a demo. The same team builds the interfaces, the pipelines and the infrastructure underneath.
Typical problems
Where this usually starts.
No evaluation on real cases
The pilot was judged on a handful of curated examples. Nobody knows how it does on last month's real inputs, so nobody dares to switch it on.
Detect
No monitoring after launch
The model drifts, the costs climb, the latency creeps up, and the team finds out from a complaint instead of a dashboard.
Predict
What we deliver
What lands in your hands.
- Backends and integrations with the systems you already run.
- Interfaces where the person stays in control and sees why.
- Built to hand over, documented, tested, yours.
- Deployment in your cloud, in EU regions or on-premise.
- Monitoring and observability for drift, cost and latency.
- Guardrails and human review on the decisions that matter.
In production
How it looks in production.
In production the software is the part your team touches every day: the screen where a reviewer accepts a draft, the API the ERP calls, the job that runs at six in the morning. It is versioned, monitored and documented like any service you already run, and it keeps working when the model is swapped for a better one.
Monitoring is the part the operations director reads twice. Drift, cost and latency sit on one dashboard, alerts reach the people who can act, and when the system is unsure it hands the case to a person with the evidence attached instead of guessing.
The four layers
Four layers. One system.
Inside this service
What this includes.
Software development
The product around the model: backends, integrations and interfaces built to last.
- Backends and integrations with the systems you already run.
- Interfaces where the person stays in control and sees why.
- Built to hand over, documented, tested, yours.
- APIs and data contracts between the model and the rest of your stack.
- Review and approval screens designed into the workflow.
- Stand-alone products and platforms, with or without a model in them.
Infrastructure & MLOps
Pipelines, inference, monitoring and MLOps that keep systems running and improving.
- An architecture review of what you have, with what to keep and what to replace.
- An evaluation harness on your real cases, run before every release.
- Data pipelines with contracts, retries and alerts.
- Deployment in your cloud, in EU regions or on-premise.
- Monitoring and observability for drift, cost and latency.
- Guardrails and human review on the decisions that matter.
- Cost control, with a budget per request you can see.
Related work
Where we have done this.
Finance
Klever's analysts stopped searching and started reviewing.
An AI analyst that reads the filings, listens to the calls and drafts the memo before the meeting.
-62%less time searching
100%memos drafted before the meeting
Manufacturing
Sand's engineers stopped guessing why a line stopped.
A system that watches the production line and explains a stoppage before an engineer has to ask.
-70%less time to find why a line stopped
100%stoppages logged automatically
Before you ask
Questions about this service.
Can you take over a pilot built by another team?
Yes. We start with an architecture review of what exists, tell you plainly what can stay and what cannot, and build from there. Taking over is common; rebuilding from scratch is rare.
Do you build software without AI in it?
Yes. If your problem is a platform, an integration or an app, that is a project for us. The same team, the same standard, no model unless the problem needs one.
Do we have to rebuild?
Usually not all of it. The model and the idea are often sound; what is missing is evaluation, integration and monitoring. We add those around what works and replace only what would fail under load.
Can you work inside our codebase?
Yes. We work in your repositories, your accounts and your review process, with your conventions. Nothing lives on our side that you cannot see.
Where will it run?
In your environment. Your cloud account, EU regions you approve, or fully on-premise when the domain requires it. We deploy into your accounts, never into ours.
Which stack do you use?
The one your team can run afterwards. We choose boring, well-supported technology by default and justify every exception in writing before we use it.
How do you handle sensitive data?
Named engineers with least-privilege access, revoked at hand-over, and every access to production data logged. Nothing trains a shared model, and nothing leaves the environment you approved.
Who maintains it after hand-over?
Your team, if you want, or us for as long as you need. Either way the documentation, the tests and the runbooks are part of the delivery, not an extra.
What does "production-ready" mean to you?
Evaluated on real cases, integrated with the systems around it, monitored for drift, cost and latency, with a person on the decisions that matter and a runbook for the day something breaks.
How do you handle testing and quality?
Automated tests from the first sprint, a review on every change and a staging environment that mirrors production. A feature is done when it runs for real users, not when it compiles.
Let's build what comes next. Together.
Tell us what you are building and what changes if it works. You get a straight answer on whether AI can solve it.
Talk to usor write to hello@maistik.studio