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SerenDB – A Neon PostgreSQL fork optimized for AI agent workloads

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SerenDB – A Neon PostgreSQL fork optimized for AI agent workloads

Show HN: SerenDB – Neon PostgreSQL fork optimized for AI agent workloads We forked Neon to make database operations faster and safer for AI agents. The goal is to enable instant experimentation with production data and catch prompt injection attacks before they hit your DB. The open-source repo is at https://github.com/serenorg/serendb The coolest current features are: 1. Time-travel queries: Query your database as it existed at any timestamp. SELECT * FROM orders AS OF TIMESTAMP '2024-01-15 14:30:00'. Essential for debugging agent decisions and auditing what data an agent saw. 2. Scale-To-Zero with pgvector: Built-in vector embeddings that sleep when idle. Pay nothing for dormant agent databases, auto-scale to 16 vCPU when needed. The coolest features in development are: 1. Prompt injection detection: Fingerprinting and context-aware policies to catch injection attempts before they reach your data. We're extending Postgres's security model to understand AI-specific attack patterns. 2. 100ms branch creation: Clone your entire production database in 100ms (vs Neon's 500ms). Enables branch-per-agent patterns and instant rollback. Great for faster testing of multiple prompt variations on real data. This is early - we're working on the hosted service now. Technical folks: curious if anyone else is hitting the "how do I safely test my agent on prod data" problem. Happy to answer questions about our updates to the branching architecture or our proposed context security approaches. Website: https://serendb.com/

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