Data platform to AI enablement
Extend your existing data platform for AI workloads without rebuilding it, so LLM systems are fed by governed, quality-checked data.
Timeline
6-12 weeks
Format
Embedded consulting alongside your data team
What you get
- Assessment of your current platform for AI readiness, including access, quality, and freshness
- Data quality gates for the sources your LLM systems depend on
- Semantic and retrieval layers that sit on top of your warehouse, not beside it
- Pipelines that keep embeddings, indexes, and knowledge bases in sync with source data
- Governance patterns for what data can and cannot reach a model
Your data platform took years to get right: tested pipelines, governed access, trusted reporting. AI features that bypass it and scrape PDFs into a vector database throw all of that away, then fail quietly when the underlying data goes stale.
This engagement connects your existing platform to your AI ambitions. We add the layers AI workloads actually need - quality gates on model-facing sources, a semantic or retrieval layer over the warehouse, and synchronization pipelines that keep indexes fresh - while keeping the governance you already have.
Good fit if you lead a data team and want AI to be an extension of the platform, not a shadow stack running beside it.