← All services Machine learning
Services
Machine learning
& AI systems
We train models, build reproducible data pipelines, and implement foundation, meta, and agent architectures — from first hypothesis to integration with your embedded, IoT, and cloud landscape.
Model training & fine-tuning
- Supervised learning for industrial data
- Hyperparameters, validation, metrics
- Export and deployment readiness
- Reproducible training runs
Data pipelines & MLOps
- ETL, labeling, feature engineering
- Training jobs, artifact versioning
- Monitoring data and model drift
- Integration with existing IoT and backend stacks
Foundation & meta-models
- Base models and domain adaptation
- Ensembles, routing, specialists per sub-task
- Cost, latency, and quality trade-offs
- On-premise, cloud, or hybrid
AI agents & orchestration
- Multi-step pipelines with supervisor control
- Tool use and secure interfaces to systems
- MCP and function calling where appropriate
- Integration into dashboards, APIs, and field devices
Stack
From data to production
Python
PyTorch, scikit-learn, pandas
Pipelines
Airflow-style jobs, CI for models
Serving
FastAPI, batch & streaming inference
LLM / agents
OpenAI-compatible APIs, MCP, RAG
LLM and agent systems in production need security by design — OWASP LLM, prompt injection, and audit logs are covered under AI security. AI security & LLM audits →
Planning ML or agents in production?
Describe your data, constraints, and target — we respond within 48 hours with an initial assessment.
Request a free assessment Reply within 24 hours No commitment Confidential