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AI & Data Engineering
We design the full data and AI stack — ingestion, pipelines, training, evaluation and deployment — so models stay grounded, monitored and production-ready.
Problems we solve
- Pilot projects that demo well but never survive production traffic
- Model outputs nobody can explain, reproduce or trust
- Data scattered across systems with no governed pipeline
What's included
- Machine learning platforms & MLOps
- LLM applications and RAG systems
- Computer vision and signal processing
- Data warehouses and real-time pipelines
- Model evaluation, monitoring and governance
- PyTorch, TensorFlow, Spark, Kafka and more
Frequently asked questions
How we work
- DiscoverWe map goals, constraints and success criteria with your team before anything is built.
- DesignArchitecture, threat model and delivery plan are agreed and reviewed while change is still cheap.
- BuildSmall senior teams ship in reviewed, tested batches with visible progress every week.
- RunWe deploy, monitor and harden the system, then hand over the runbooks — or keep operating it with you.