80%
“cost savings of data storage, amounting to approximately 80% savings since using Pinecone”
Tal como se publicó en pinecone.io. Capturado por usedby el 8 oct 2026.
Qué pasó
InpharmD uses Pinecone as the vector database behind its AI assistant Sherlock, storing embeddings of medical literature documents so relevant drug information can be retrieved quickly for clinicians' questions as part of a retrieval augmented generation workflow.
Resumen escrito por usedby a partir de la página de origen, en inglés. Las cifras son de Pinecone y de InpharmD, no nuestras.
- 95 times faster“The response time to user inquiries has seen a remarkable 75% reduction, with the first response time now 95 times faster.”
- 70%“The adoption of Pinecone has led to a significant 70% improvement in result accuracy, providing more precise and contextually relevant answers.”
- 2 billion“Pinecone indexing and search for over 2 billion vectors simultaneously provides InpharmD with the necessary long-term memory to continue expanding and incorporating additional medical literature into their dataset.”
Pinecone serves as the core database infrastructure for Sherlock, playing a crucial role in storing and processing vector embeddings for the efficient retrieval of relevant medical information during clinical inquiries.
Pinecone is integral to our data-driven operations. Its seamless scalability, rapid query results, and impressive low latency make it an indispensable asset in enhancing efficiency and productivity
Lo que dice la historia, y lo que verificamos
Comparamos la historia con su página en línea el 8 oct 2026.
- La cifra: 80%VerificadoImpresa palabra por palabra en la página, cerca del nombre de InpharmD.
- El pasaje citado arribaVerificadoCopiado palabra por palabra de la página, cerca del nombre de InpharmD.
- InpharmD usa PineconeVerificadoLínea de nivel Confirmado. Última verificación entre todas las fuentes: 8 oct 2026.
- El resultado en síNo verificadoLo citamos; no lo medimos.




