Suprflo

Suprflo offers a sophisticated memory layer designed to manage conversational facts for autonomous systems. Key capabilities include: * Fact extraction from conversations * Bi-temporal storage for full historical context * High-accuracy recall (92.1% LoCoMo) * Postgres-native data management * Openly benchmarked and verifiable performance This system addresses the challenge of stateless conversational systems by ensuring that critical user information and preferences are not lost between interactions. It captures details like dietary restrictions or past preferences, allowing for persistent and context-aware interactions without repeatedly asking for information. The bi-temporal design means that facts carry validity windows instead of being overwritten, providing a complete audit trail and enabling queries about past beliefs. Suprflo eliminates the need to stuff entire conversation histories into prompts, which is both expensive and unscalable. By intelligently extracting and storing relevant facts, it reduces query costs significantly and overcomes context window limitations, making long-term user engagements practical. Every raw turn is preserved alongside extracted facts, establishing a recall floor where the original words can always be retrieved, preventing silent loss of information. This tool is ideal for developers building sophisticated conversational applications that require persistent memory, verifiability, and accurate information retrieval over time. It ensures that user experiences are consistent and personalized across multiple sessions, enhancing engagement and reducing friction.