StartupVenture-backed
Engram
A learned memory layer for enterprise agents that prepares memories ahead of time to cut token costs.
Engram builds a learned memory layer for enterprise AI agents. Its CEO, Dan Biderman, says the approach can "prepare memories ahead of time instead of pasting them on the fly", reducing what agents must load into context. It came out of stealth in June 2026 with $98M from investors including General Catalyst, Kleiner Perkins, Sequoia and Factory.
People
Researcher
Co-founder
Context engineering & memory
Researcher
Co-founder
Context engineering & memory
Co-founder & CEO
Context engineering & memory
Co-founder & CTO
Context engineering & memory
Neighbours in the directory
Berkeley, CA · Est. 2024
Stateful agents with memory, from the team behind MemGPT.
Letta (formerly MemGPT, out of UC Berkeley) builds an agent server with built-in memory, context management and state — letting agents persist, learn and be edited like files rather than living in a chat window.
$10M seed led by Felicis (2024)
San Francisco, CA · Est. 2024
The memory layer for AI apps and agents.
Mem0 (from the EmbedChain team) provides a managed + open-source memory layer that extracts, stores and retrieves user and entity memories across sessions — a standard building block for personalization.
San Francisco, CA · Est. 2023
Long-term memory for agents, built on temporal knowledge graphs.
Zep maintains durable, time-aware agent memory via its open-source Graphiti engine — facts, relationships and their history — so conversations and tasks can span sessions.
Connections
Relations from the Harness Hub knowledge graph, as charted in the State of Harness reports.
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Sources
Verified Oct 29, 2026