Retrieval Swap Readiness
Retrieval Swap Readiness treats the retrieval layer as a replaceable component and measures how cheaply an agency can move a client's grounded AI workload from one provider to another.
By InnovaAI ResearchPublished Updated
What is Retrieval Swap Readiness?
“Retrieval swap readiness → client retention leverage”
Retrieval Swap Readiness treats the retrieval layer as a replaceable component and measures how cheaply an agency can move a client's grounded AI workload from one provider to another. The framework has three tests: can the same document set be re-indexed inside a week, does the evaluation harness score answers independently of the vendor, and does the client contract name retrieval quality as a deliverable rather than a hidden dependency. Agencies that pass all three keep pricing power because they can walk when accuracy or cost drifts. Ragie's context engine API handles parsing, entity extraction, and multimodal ingestion as a managed layer, which shortens the re-index step but also concentrates risk if it becomes the only path. ai·rete·rag shows the opposite posture: a Rete rule engine decides outcomes deterministically while retrieval only grounds the explanation, so swapping the retrieval source changes wording, not decisions. That separation is the pattern worth copying into client delivery.