How Fieldy AI Achieved Reliable AI Memory with Qdrant

Fieldy AI, a wearable AI note-taking device that records and transcribes conversations into a searchable memory, faced reliability challenges with its initial vector database, Weaviate, due to persistent operational errors affecting data integrity and user trust. To resolve these issues, Fieldy migrated to Qdrant, a vector database known for its stability and suitability for self-hosted deployment, which eliminated query failures, reduced latency, and cut infrastructure costs by two-thirds, while scaling to handle tens of millions of embeddings. The migration process was efficient, leveraging existing vector schemas and updating backend API calls to enhance performance. With enhanced reliability and cost efficiency, Fieldy's engineering team is now focused on improving retrieval quality by introducing advanced filtering and embedding strategies to refine search results and enhance the device's memory recall capabilities.

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