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On-device information retrieval

Published : Nov 05, 2025
NOT ON THE CURRENT EDITION
This blip is not on the current edition of the Radar. If it was on one of the last few editions, it is likely that it is still relevant. If the blip is older, it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar. Understand more
Nov 2025
Assess ?

On-device information retrieval is a technique that enables search, context-awareness and retrieval-augmented generation (RAG) to run entirely on user devices — mobile, desktop or edge devices — prioritizing privacy and computational efficiency. It combines a lightweight local database with a model optimized for on-device inference. A promising implementation pairs sqlite-vec, a SQLite extension that supports vector search within the embedded database, with EmbeddingGemma, a 300 million parameter embedding model built on the Gemma 3 architecture. Optimized for efficiency and resource-constrained environments, this combination keeps data close to the edge, reducing dependence on cloud APIs and improving latency and privacy. We recommend teams assess this technique for local-first applications and other use cases where data sovereignty, low-latency and privacy are critical.

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