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Data

A privacy-centric architecture combining SQLite for relational notebook storage and FAISS for high-performance: on-device vector indexing.

This stack prioritizes data sovereignty by running all operations on local hardware. SQLite manages the relational schema for notes and metadata (maintaining strict ACID compliance) while FAISS handles similarity searches across high-dimensional embeddings. The setup delivers sub-10ms query speeds and full offline capability. It is the definitive choice for building secure: personal AI knowledge bases where speed and privacy are the primary requirements.

https://faiss.ai
8 projects · 8 cities

What builders pair with Data

Projects using both technologies. Select a pairing to see a project.

Built with Data
Hugging Face 2 shared projects Inference 2 shared projects OpenAI API 2 shared projects Python 2 shared projects TypeScript 2 shared projects ABBYY FineReader 1 shared project
12 more pairings
AI models 1 shared project Amazon Textract 1 shared project Azure Databricks 1 shared project Azure Data Lake Gen2 1 shared project Azure DevOps 1 shared project Azure Machine Learning 1 shared project Backend 1 shared project Beads 1 shared project Beads (Go) Dolt (like Git for mysql 1 shared project BullMQ 1 shared project Claude Code 1 shared project Cloud Vision API 1 shared project

Pairing: Hugging Face

Inside Compar:IA — Exploring the dataset of 150K conversations & 100K preferences from a French chatbot arena

Paris · June 26, 2025

view project | view Hugging Face

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