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Home / Infrastructure design / Data and retrieval
Ingestion, embedding pipelines, a vector store and retrieval, built so the answers a model gives are grounded in your data rather than its memory.
What it is
Ingestion, embedding pipelines, a vector store and retrieval, built so the answers a model gives are grounded in your data rather than its memory.
Documents and records pulled in, cleaned and chunked.
Storage sized for the corpus and the query pattern.
Hybrid search and reranking, tuned against real questions.
A user only retrieves what they were already allowed to read.
How it works
In the field
What the work looks like once it is on the floor.


Detail
| Sources | Files, databases, wikis, ticket systems and object storage. |
|---|---|
| Embedding | Batch and incremental, with re-embedding when the model changes. |
| Store | Vector store sized to corpus and latency target. |
| Retrieval | Hybrid keyword and vector search with reranking. |
| Evaluation | A test set of real questions, scored before and after changes. |
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Support
Fixed price against a defined scope. Ongoing operation is quoted separately as a monthly service.
We specify it and can procure it, but it stays on your balance sheet.
Yes. Design and build are delivered white-label where a partner holds the customer.
Next step
An hour with our engineers, no charge. Bring a floor plan, a workload, or just the problem.