·4 min read
Designing an AI-ready data layer
Before you bolt an LLM onto your app, get the data underneath it into a shape models can actually use.
dataarchitecture
Models are only as good as what they read
Most AI projects stall on the data, not the model. Documents live in seven tools, schemas drift, permissions are unclear.
What "AI-ready" means in practice
- One canonical place per entity, with a stable ID
- Change streams so embeddings stay fresh
- Row-level access carried through to retrieval
- Audit trails for every model-driven write
Start small
Pick one domain — customers, tickets, documents — and get that clean before you generalize. The second domain takes a third of the time.
