Services
AI and data solutions.
We build systems that learn from data, support decisions and automate work.
AI and data is the Meybrain Technologies service area for systems that learn from your data, support decisions and automate repetitive work.
01 / Definition
What we do in AI and data.
It covers machine learning models, large language models and AI agents, data analytics and reporting, and process automation. What these have in common is that the outcome is working software inside your daily operations, not a slide deck.
AI projects usually fail when they start with the technology and go looking for a problem. We start from the other end: which decision should be better, and which task should take less effort? If AI is the right answer, we use it; sometimes the right answer is a good report or a simple rule.
02 / Services
Services in this area.
- 01
Machine learning
Demand forecasting, churn prediction, anomaly detection, classification and recommendations.
- 02
LLM applications and AI agents
Assistants that answer from your documents with citations, customer chat, and agents that act with human approval.
- 03
Data analytics and reporting
Scattered data turned into self-updating dashboards built on agreed definitions.
- 04
Process automation
Approvals, document processing, validation and notifications handed to software.
03 / Where to start
Where to start, by question.
| Your question | Starting point |
|---|---|
| "How much will we sell next month, and how much stock should we hold?" | Machine learning |
| "Which document says this, and what should we tell the customer?" | LLM applications and AI agents |
| "Why don't the sales and finance numbers match?" | Data analytics and reporting |
| "Why are we still doing this by hand?" | Process automation |
If you are not sure where to begin, technology and AI consulting lets us assess the opportunities with you first.
04 / Audience
Who it is for.
- Companies that have collected data for years but cannot use it to decide.
- Businesses whose teams lose time to repetitive messages, data entry and report building.
- Organisations working with heavy documentation or regulation that need the right answer quickly.
- Software companies and start-ups adding AI features to their products.
05 / How we work
How we work.
- 01
Start from the business question
What should improve, and how success is measured.
- 02
Compare with a simple baseline
Every model is tested against today's method or a simple rule, and we say so if it does not help.
- 03
Make quality measurable
LLM projects get an evaluation set of real questions, re-run on every change.
- 04
Keep people at the decision points
Approval and exception screens wherever errors are costly.
- 05
Handle privacy first
Where data is processed, which provider sees it and KVKK or GDPR requirements are settled during architecture.
- 06
Build in monitoring
Alerts for model quality, cost and data drift are part of the delivery; follow-up after launch is an option.
06 / Examples
Examples from our work.
- 01
Kentsel Dönüşüm AI
Our assistant for property owners going through urban renewal in Türkiye, with legal summaries, calculators and province guides; live on the web and the App Store.
- 02
BeinStory
Our literature platform where readers talk with book characters and authors through AI; live on the web, iOS and Android.
- 03
İmarsal
Our product that turns a block and parcel number into a zoning lookup, floor-area calculation and AI-assisted feasibility; in launch preparation.
All three are our own products; see the portfolio.
07 / Questions
Frequently asked questions.
- 01
Where should an AI project start?
With one task that repeats often, has data behind it and has a measurable result. A small, clear first project earns your team's trust and gives real cost and benefit figures for the next investment.
- 02
Which AI models do you use?
We are not tied to one provider. We choose between commercial model APIs and open models that can run on your servers based on quality, cost and data location, and build so the model can be changed later.
- 03
How is our data kept private?
We decide with you where data is processed: on your servers, in your cloud account or with a model provider whose terms suit you. Flows that involve personal data are reviewed against KVKK or GDPR at design stage.
- 04
Does AI make sense for a small company?
Often yes, but not as a big project. Automating one task, such as reading documents, sorting requests or preparing a regular report, can make a noticeable difference even in a small team.