AI & Data
Data platform engineering
Warehouse, pipelines and data quality — the foundation most AI projects discover they are missing.
Who it is for
Mid-market with messy data.
Everything below is in the scope document, written and priced before anything starts. If something you need is not on this list, say so and it goes in the quote — or we tell you it does not belong in this engagement.
- Warehouse or lakehouse design on your existing cloud
- Ingestion and transformation pipelines with tests, not just schedules
- Data quality checks and lineage, so a wrong number can be traced
- Access model and PII handling designed for DPDP and GDPR simultaneously
- Handover documentation your own team can operate from
Also in AI & Data
AI readiness assessmentWhat is worth automating, what it costs at real volume, and the two things that will block you.2–3 weeksAI governance, EU AI Act & ISO 42001 readinessRisk classification, a gap analysis and a control set your auditor and your EU customer will both accept.3–5 weeksRAG & knowledge assistantsRetrieval over your own documents, built on your permissions model rather than around it.6–10 weeksAI agents & workflow automationAn agent inside an ops-heavy process, with the human checkpoints designed in rather than asserted.6–12 weeks
Next step
Thirty minutes on whether this is the right engagement.
If a different service on this list fits better, or if you do not need us at all, that is what the call will conclude.