Telecommunications
An operator's network produces more alarms, traffic data and customer interactions than any team can follow. AI can help find faults faster, plan capacity, answer subscribers' questions and understand why they leave. It runs on the operator's own infrastructure and has to work with equipment from different vendors.
Challenges
Data stays with the operator
Subscriber and network data is subject to strict rules and usually has to stay on the operator's own infrastructure, so the models have to run there too.
Systems work across vendors
Networks combine equipment and management systems from different vendors. AI has to read data from all of them and send results to the tools operations teams already use.
Results hold up at network scale
Networks produce large volumes of data around the clock and change as new sites and technologies are added. Systems have to keep up and stay accurate as the network changes.
Typical problems
Network monitoring and fault management
Grouping related alarms during an alarm flood, pointing to the likely root cause and spotting unusual behavior in network data early.
Capacity planning
Forecasting traffic by region and site, and planning capacity and investment from it.
Customer service
Assistants that answer subscribers' questions about bills, plans and service problems, and pass complex cases to a support representative.
Churn analysis
Spotting subscribers who are likely to leave and understanding the reasons from usage, complaint and billing data.
Field operations
Prioritizing faults, planning field teams' work and giving technicians the information they need before they go on site.
Our research areas
See all research areasWorking with sensitive data
Training and running models on subscriber and network data without it leaving the operator.
Foundation models
Open-weight language models adapted to Turkish and to the language of network operations and customer service.
Controlled agents
Agents that gather data from network systems and prepare fault analyses, with every step checked and logged.
Interpretability & evaluation
Measuring how accurate alarms and forecasts are, and showing the data behind each one.
Related services
All services- Anomaly & fraud detectionSystems that flag the unusual transactions, failures and faults worth a closer look, even with few confirmed examples.
- Time series forecastingForecasts of demand, load, capacity and sensor values that show how certain they are.
- AI assistantsAssistants that answer from your own documents and systems, with sources and access control.
- AI agentsAI agents that carry out defined tasks in your systems, within permissions and approval steps you control.
- Decision optimizationSchedules, routes, prices and stock plans that respect your constraints and leave planners in control.
- LLM deploymentLanguage models running on your own servers or private cloud, sized and secured for your workload.
Work with us
Work usually starts with one region, one network domain or one customer service process, and the system runs on the operator's own infrastructure. Once the results are measured, the scope can extend to other regions and processes.
R&D projects
For problems with no proven solution yet. We test approaches on your data and work toward a prototype in agreed milestones. At each milestone we tell you plainly what looks feasible and what doesn't.
Software development & consulting
For problems with known solutions. We build production software on proven methods, or advise your team on architecture, tooling and model choice.
Funded research
Joint R&D projects backed by national and international research funding, with industry and academic partners.
Corporate training
Training programs tailored to your team. Topics include everyday work with AI assistants, product development, integration and strategy.
Frequently asked questions
Does subscriber data leave the operator?
No. Models run on your own infrastructure, and subscriber and network data stays there.
Can AI work with network equipment from different vendors?
Yes. It reads data from the systems you already use, whichever vendor they come from, and sends results to your existing tools.
Does the AI make changes to the network?
Not unless you want it to. The system finds problems and suggests actions; changes to the network are made or approved by your engineers.
Where should a telecom operator start with AI?
Usually with a high-volume task whose results are easy to measure, such as alarm grouping in one region or the most common customer questions.
Who runs the system after handover?
Your own teams. The system is handed over with its documentation, and we can also provide support after that if needed.
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