For developers building AI agents that need to remember past interactions, Redis Agent Memory is a managed memory server that uses LLMs to extract key facts from conversations, stores them for short and long-term recall via vector search, and caches responses with LangCache.
Presence & Market Position
Tracked · below panel floor — earned mentions are accruing toward the next scored window.
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Redis Agent Memory is positioning itself as the managed memory layer for AI agents, extracting useful facts from conversations and making them available for short- and long-term recall. Its market footprint is early, with no distinct practitioner conversation established around the product yet. The product builds on Redis’s role in fast data access by combining vector retrieval, response caching through LangCache, and interfaces for agent frameworks through its API, MCP server, and SDK. That gives developers a focused way to persist context across sessions without building a separate memory service.
Neo4j Agent Memory
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ElevenLabs
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Business Profile
Redis Agent Memory is a product line inside Redis, the in-memory data platform founded in 2011 that has grown to roughly 1,500 employees and reported $300M+ in ARR as of January 2026. The memory server emerged from Redis's broader 2025 push into AI infrastructure, the same window that produced its Iris context engine, LangCache, and the Decodable acquisition, and is available as an open-source server on GitHub, a private-preview self-managed build for Redis Software, and a hosted service on Redis Cloud. It carries no separate financial or funding history of its own; its trajectory tracks Redis's broader AI-agent product build-out.
Employees & founded inherited from Redis (parent).
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
Redis Agent Memory ships as a two-tier memory system, session-scoped working memory and vector-backed long-term memory, with automatic background extraction and deduplication from conversation events. It exposes a REST API and Python SDK with tool abstractions for OpenAI and Anthropic, plus an MCP server for direct assistant integration. Deployment spans an open-source self-hosted server, a private-preview self-managed build for Redis Software, and a managed service on Redis Cloud.
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