RESEARCH & ENGINEERING BLOG
Technical deep dives and architecture patterns on building production memory layers for AI agents. The evaluations are open and reproducible.
Agents that run for months fail in ways a short demo never shows. Memory piles up, old facts linger, and recall slowly gets worse as the store grows.
A vector database does similarity search over embeddings. That is a retrieval primitive, not a memory system. Here is what memory needs that it does not do alone.
RAG and memory both feed text into the prompt, so they get confused. RAG grounds answers in shared documents; memory tracks what changes about one user over time.
AI agents forget between sessions because language models are stateless. Here is why resending the chat transcript only works for a while, and what real memory takes.
PRODUCTION AI MEMORY ENGINE
Bi-temporal facts, Postgres-native pgvector storage, and sub-50ms hybrid recall for enterprise agent workloads.
Suprflo is a product of ATIIAD Technologies Pvt. Ltd. (trading as Baaz). Questions: hq@suprflo.com.