memgram

memgram is an AI developer tool that provides observable, controllable memory infrastructure for production AI agents. AI agents accumulate preferences, history, decisions, and context over time, and memgram turns those interactions into memory you can retrieve, inspect, and govern rather than treating memory as a black box. Its memory pipeline runs a visible sequence of steps for each interaction, including extract, classify, deduplicate, and decide, and it records why something was stored, retrieved, or superseded, so teams can see when a new fact supersedes an old one or when two memories contradict each other on the same question. It exposes inspectable runtime state per scope (such as a specific user or enterprise account), tracks active constraints, facts, and status with confidence scores, and logs events including how many memories were persisted versus rejected along with trace latency. memgram is designed to run memory in production with options like VPC deployability, an open-core model, and OpenTelemetry compatibility, and it ships templates for common agent types. Backed by Techstars NYC and now in public beta, it is aimed at AI engineering teams building agents that need reliable, auditable memory.

AI engineering teams use memgram to run observable, governable memory for production agents so they can inspect what was stored, retrieved, and why.