AI consulting
that ships.
We’re a technical team in Istanbul. We build AI systems that go to production — fraud detection, demand forecasting, predictive maintenance. If you have a real problem and real data, we should talk.
20+
Projects shipped
99.7%
Best model accuracy
<50ms
Inference latency
8-16wk
Avg. delivery
What we do
Three things,
done well.
We don’t do everything. We do ML engineering, data infrastructure, and technical strategy. That focus is why our projects actually make it to production.
See detailsMachine Learning Development
Custom models for your specific problem. Fraud scoring, demand forecasts, churn prediction, anomaly detection. We handle data pipelines, training, evaluation, and deployment to production with monitoring.
Python, PyTorch, TensorFlow, Kubernetes, MLflow
Data Engineering & Analytics
The foundation that makes ML possible. We build data pipelines, set up warehouses, connect fragmented sources, and create dashboards that people actually use. No AI works without clean data — we start here.
Spark, Airflow, dbt, Snowflake, BigQuery
AI Strategy & Advisory
Honest assessment of where AI fits your business — and where it doesn’t. We identify high-impact use cases, scope realistic timelines, and help you avoid expensive mistakes. No 80-slide decks with buzzwords.
Workshops, roadmaps, technical due diligence
Featured work
Fraud detection for a Turkish bank
A top-five bank was losing millions to fraud with a rule-based system that flagged 12% false positives. Their fraud team spent more time reviewing legitimate transactions than catching real ones.
We replaced it with a real-time ML pipeline — gradient-boosted trees for known patterns, deep anomaly detection for novel attacks. The system processes transactions in under 50ms with continuous retraining on new fraud vectors.
What changed
- False positives dropped 45%, freeing up the review team
- Detection accuracy went from ~88% to 99.7%
- Processing latency under 50ms per transaction
- Model retrains automatically on flagged data weekly
Stack
Python, TensorFlow, Apache Kafka, Kubernetes, PostgreSQL
Timeline
14 weeks, discovery to production
How we work
No magic. Just a process
that respects your time.
Understand the problem
We start with your business problem, not our technology. What are you trying to improve? What data do you have? What does success look like? This takes 1-2 weeks and saves months.
Prove it works
Build a minimal version on real data. If the model can’t beat your current process on a test set, we stop and tell you. No sunk cost projects that limp into production.
Ship it
Production deployment with monitoring, alerting, and retraining pipelines. We hand over working infrastructure, not notebooks. Your team can maintain it without us.
Measure and iterate
Track real business metrics, not just model accuracy. If the system isn’t delivering value, we adjust. Ongoing support available but not required.
Most AI projects fail because they solve imaginary problems. We only take on work where the data exists, the problem is real, and the team on the other side cares about the outcome.
Ensar Bera Tuncel
Founder, Akilion
Have a project in mind?
Tell us about your problem. We’ll be honest about whether we can help — and if we can’t, we’ll point you in the right direction.
Get in touch