AI, ML & Data for serious teams
AI and data engineers who build eval-driven RAG, agents, and ML pipelines — not notebook demos. EU-hosted options, observability, and guardrails baked in from sprint one.
What clients actually get
No vanity metrics — measurable business outcomes our engagements consistently deliver.
Eval suites and hallucination controls on every LLM feature
Reproducible training and deployment pipelines
Clear data residency and retention policies
Every capability under AI, ML & Data
Pick a role to explore vetting, engagement models, tech focus, and FAQs.
AI / LLM Engineer
Hire a vetted senior AI / LLM — European time zones, production-grade delivery, embedded in your sprint cadence within days.
Machine Learning Engineer
Hire a vetted senior Machine Learning — European time zones, production-grade delivery, embedded in your sprint cadence within days.
MLOps Engineer
Hire a vetted senior MLOps — European time zones, production-grade delivery, embedded in your sprint cadence within days.
Data Engineer
Hire a vetted senior Data — European time zones, production-grade delivery, embedded in your sprint cadence within days.
Data Scientist
Hire a vetted senior Data Scientist — European time zones, production-grade delivery, embedded in your sprint cadence within days.
Computer Vision Engineer
Hire a vetted senior Computer Vision — European time zones, production-grade delivery, embedded in your sprint cadence within days.
NLP Engineer
Hire a vetted senior NLP — European time zones, production-grade delivery, embedded in your sprint cadence within days.
A modern, proven foundation
We pick boring, battle-tested tools so your platform stays maintainable five years from now.
Highlights
- LLMs, RAG, agents, and fine-tuning workflows
- MLOps, feature stores, and model monitoring
- Computer vision and NLP in production
How a ai, ml & data engagement runs
- 01
Discovery
Structured workshop mapping goals, users, constraints, and success metrics.
- 02
Architecture
ADR-driven design — references, trade-offs, and a clear path to production.
- 03
Build
Weekly demoable increments, written tests, and code reviews. No surprises at launch.
- 04
Launch
Hardened deployments, observability, runbooks, and a clear rollout/rollback plan.
- 05
Iterate
Post-launch we track usage, fix friction, and ship improvements on a cadence.
Ready to build with AI, ML & Data?
Send us a brief — you'll hear back within one business day with next steps and a senior architect on the call.