/0.3 / Data Ops
The foundation everything else runs on.
Most AI projects fail because the data isn't ready. We treat data engineering as the first-class discipline it is. Before a model is trained, before an agent is wired, the pipelines are clean, versioned, monitored, and replayable.
We build on the stack you already have. Azure, AWS, GovCloud, on-prem, air-gapped. We leave you with the runbooks, tests, and dashboards to own it. No proprietary middleware. No vendor lock-in.
The checklist is unglamorous and non-negotiable: schema contracts, lineage tracking, freshness monitors, null-rate alerts, access controls, audit trails, retention policy. When the data layer is boring and predictable, everything downstream becomes possible.
What we build
- —ETL/ELT pipelines with schema contracts and data-quality tests.
- —Observability: lineage, freshness, null-rate monitoring, alerts.
- —Governance: access controls, audit trails, retention policy.
- —Infra that runs on your cloud. Azure Gov, AWS GovCloud, on-prem.