A 5-day engagement that maps your data, surfaces high-ROI AI candidates, and recommends a pilot — fixed price.
Read the briefFrontier-class models on isolated infrastructure — your data never leaves the perimeter.
Explore the stackLakehouses, ETL pipelines, analytics, and data observability — the foundation under any AI deployment.
Every failed AI project traces back to the same root cause: data that’s scattered, stale, or untrusted. We build the lakehouse, pipelines, and observability that make everything above them possible.
Open table formats (Iceberg/Delta), reliable transformation with dbt, and the right serving engine per query profile — so your data is one trustworthy source, not ten conflicting ones.
Specific, production-grade capability — not a feature checklist.
Iceberg / Delta on S3, GCS, MinIO, or on-prem — open formats, no lock-in.
Orchestrated ETL/ELT with tests, lineage, and backfills you can trust.
dbt for modelled, documented transforms; custom Python where dbt stops.
Postgres, ClickHouse, or DuckDB chosen per query profile, not dogma.
Freshness, volume, and schema monitoring so breakages surface before dashboards lie.
Clean, governed data with the metadata RAG and agents need.
We catalogue your sources, quality, and consumers, then design the lakehouse and models.
Orchestrated, tested ingestion and transformation with full lineage.
dbt models feed the serving engine chosen for each workload.
Data-quality monitoring catches freshness, volume, and schema issues early.
Start with a fixed-price 5-day Readiness Assessment or a 6-week pilot. Senior engineers, measurable evals, and a system you own on handover.