Reviews and approvals
Contracts, claims and applications that someone reads in full before anyone can say yes. The system reads first, flags what matters and drafts the answer.
Read
AI
Teach a system to do the work your experts do by hand.
Models, agents and automation built around your data and your rules, for a process you already run.
Typical problems
Where this usually starts.
Estimates and pricing
Quotes priced from memory and last year's spreadsheet. The system prices from your own history and explains every line.
Predict
Monitoring and inspection
Lines, sensors and cameras watched by people who cannot watch all of them at once. The system flags the anomaly before it becomes downtime.
Detect
What we deliver
What lands in your hands.
- Fine-tuned and domain models, trained on your examples.
- Agents with tools and approval steps built into the workflow.
- Retrieval over your documents, with every answer cited to its source.
- Computer vision for inspection, counting and reading.
- Forecasting and anomaly detection on your own history.
- An evaluation harness on real cases, run before and after launch.
- Integration into the systems your team already uses.
In production
How it looks in production.
In production the system sits inside the tool your team already opens every morning. A reviewer sees the draft, the flags and the sources side by side, accepts or corrects in one click, and every correction becomes a labelled example the model learns from at the next retraining.
When the system is unsure it says so. Cases below the confidence threshold go to a person with the evidence attached, nothing is decided in silence, and the operations lead can see the volume, the accuracy and the exceptions of the week on one screen.
The four layers
Four layers. One system.
Inside this service
What this includes.
AI development
Custom models, agents and RAG systems, trained on your data and shipped to production.
- Fine-tuned and domain models, trained on your examples.
- Agents with tools and approval steps built into the workflow.
- Retrieval over your documents, with every answer cited to its source.
- Computer vision for inspection, counting and reading.
- Forecasting and anomaly detection on your own history.
- An evaluation harness on real cases, run before and after launch.
- Integration into the systems your team already uses.
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
Legal
A legal-tech platform reviews a contract in half the time.
A reader that flags the clauses a lawyer needs to see and drafts the review note, inside the platform its users already trust.
-45%less time reviewing a contract
92%of flagged clauses confirmed by a lawyer
Construction
Mosaic estimates a job in a third of the time.
A model that reads the drawings and quantities, an estimating agent and a draft estimate the estimator corrects.
-38%less time producing an estimate
±6%deviation from final cost
Before you ask
Questions about this service.
Do we need clean data?
No. We start from the data the process already produces, messy as it is, and clean only what the first result needs. Waiting for perfect data is how most projects never start.
What if the model is wrong?
It will be, sometimes. That is why every system we ship measures its own confidence, escalates the cases it is unsure about to a person and logs every decision so a mistake can be traced and corrected.
Can it work with our existing tools?
Yes. The answer, the draft or the alert lands where the work happens today, inside your ERP, CRM, ticketing tool or inbox. Integration is part of the build, not an add-on.
How do you measure quality?
Against your real cases. Before the build we agree on a number that matters to the team, we test the system on past examples and we keep measuring it in production, so quality is a dashboard, not an opinion.
What happens after launch?
We stay. Monitoring, retraining and improvements from real use, for as long as you want us to. The documentation and the hand-over are designed from the first sprint so your team can run it without us.
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