Finance
Klever's analysts stopped searching and started reviewing.
-62%less time searching
100%memos drafted before the meeting
About Maistik
We build the intelligence behind difficult work.
Maistik is an AI development studio based in Valencia. We design, build and deploy custom AI systems for businesses where the work is difficult and a wrong answer is expensive.
Why we exist
Most AI is built to impress. We build it to work.
Maistik exists for the gap between a demo that impresses and a system your team runs every day.
- Demos
A demo is not a system.
It runs on chosen examples, in a quiet room, with the builder at the keyboard. Your work happens on messy data, under real constraints, with people who did not build it.
- Answers
A wrong answer costs more than no answer.
We build for the work where a mistake is expensive: contracts, inspections, estimates, filings. The system has to be right, or say that it is not.
- Pilots
Pilots have to end.
Too many AI projects live forever as a pilot: nobody owns it, nobody measures it, nobody switches it off. We build to hand over, with monitoring and a number that says whether it works.
Our approach
We don't start with AI. We start with the problem.
We understand the work before we decide what technology belongs in it. The people, the data, the constraints, the decisions. Only then do we apply AI, where it makes sense.
01
Understand
We immerse in your business, data, users and constraints to frame the problem worth solving.
02
Prove and design
A working prototype on your real data, plus the architecture and experience decisions. You see it before we build it.
03
Build and integrate
We train, integrate and ship into your systems, with evaluation from day one so quality is measured, never assumed.
04
Scale and improve
We deploy, monitor and keep improving the system with what it learns in real use.
The Maistik system
One system. Four layers.
The right intelligence only works when everything around it works too.
- Product
Intelligence is only useful where the decision is made. We deliver it inside the tools people already use, as an answer, an alert or an automatic action, with the evidence one click away.
- Agent
The agent turns a prediction into work done. It follows a task from start to finish, handles the routine, escalates the exceptions, and shows its reasoning so a person can check it in seconds.
- Model
This is the intelligence: a model trained on your data to do one thing very well. Read, predict, detect or see, depending on the problem. Not a generic chatbot; a specialist for your business.
- Data
Every business produces data all day without noticing. Documents, numbers, readings, images. We start there: nothing new to collect before the first result.
Our standard
Good AI is less about the model. More about the system around it.
The difference is in the architecture
The same model gives a different answer inside a system built for your data. That is where the work is.
Evaluation from day one
A number you measured on your cases, before launch and on a schedule after it.
The person decides
The system reads, ranks, drafts and flags. The decision stays with someone who can defend it.
No platform, no lock-in
You own the code, the models and the data. Nothing here needs us to keep running.
Production is the product
Monitoring, retries, a review queue and a hand-over are the deliverable, not the appendix.
What we don't do.
AI for AI's sake.Black-box systems.Endless pilots.Technology nobody uses.
Experience
Built for real operations.
From industrial environments to knowledge-heavy workflows, we help teams turn complex problems into systems that run every day.
- Read the case
- Manufacturing
Sand's engineers stopped guessing why a line stopped.
Read the case-70%less time to find why a line stopped100%stoppages logged automatically - Legal
A legal-tech platform reviews a contract in half the time.
Read the case-45%less time reviewing a contract92%of flagged clauses confirmed by a lawyer
Who leads the work
One lead per project. Accountable end to end.
Every project is led by one of us, someone who has already taken a model to production. Around that lead, the engineers, data and product people the system needs, sized to the work, not to a headcount.
Ana Pérez
Lead ML engineer
Ana has taken models to production in logistics, energy and finance. She writes about evaluation and the unglamorous parts of shipping AI.
Marcos Ruiz
Product engineer
Marcos designs the interfaces around AI systems: the parts people actually touch. He has shipped internal tools for logistics and industrial teams.
Brand & media
Everything you need to write about Maistik.
Logos, boilerplate and images for press and partners.
Open the media kit
Bring us the difficult problem.
We'll tell you plainly whether AI is the right tool, and what we'd build first.
Talk to usor write to hello@maistik.studio