Relevance AI Memory

https://relevanceai.com/docs/agent/build-your-agent/memory

Two memory scopes: conversation metadata (KV per-conversation) and persistent memory (cross-session). Enabling metadata auto-adds Add/Read conversation metadata tools.

Active · Verified 2026-10-22 · fresh as of 2026-10-22 · 43 cited facts, 4 with a third-party source · 2 recorded changes · Suggest a correction

At a glance

Tier
T1
Latest release
not applicable — not OSS fix
License
not applicable — not OSS fix
GitHub
not applicable — no GitHub repo fix
Freshness
2026-10-22 fix
Layer
agent-infra repo fix
Licensing
commercial vendor fix
Deployment locus
cloud vendor fix
Platform vs product
platform vendor fix
Accelerator
aws-genai-accelerator-2024 third-party fix
Protocols
mcp-client, mcp-server vendor fix

Memory taxonomy

storage
kv
retrieval
injection
persistence
cross-session
update
overwrite
unit
fact
governance
inspectable
conflict
overwrite

When to use

Optimised for: low-code agent platform + dual-scope memory

Anti-fit: searched not found

Pros & cons

Pros

No-code agent platform with memory built in — fastest path to a deployed agent for non-engineers.

Cons

Memory abstractions are simple; sophisticated agent designs hit ceilings quickly.

Claims & capabilities

Free 200 actions/mo; Pro $19/mo; Team $234/mo.

Technical surface

API surface
searched not found
Backend storage
searched not found
Deployment
Managed cloud only (SaaS); multi-region on enterprise tier
Embedding model
searched not found
Multi-tenancy
searched not found
MCP
yes — hosted MCP server at mcp.relevanceai.com exposing agents/tools/knowledge to Claude, ChatGPT, Cursor etc. (OAuth, role-scoped); MCP client for external servers also documented
A2A
searched not found
OpenTelemetry
searched not found

Similar systems

Other framework-embedded memory in the catalog, ranked by inbound references.

  • Spring AI ChatMemory T3

    Wraps conversation memory behind an Advisor abstraction. MessageWindowChatMemory default 20-msg sliding window (preserves system messages); pluggable ChatMemoryRepository backends (in-memory, JDBC, Cassandra, Neo4j). Memory injected as cross-cutting concern at the ChatClient level.

  • Flowise Memory T1

    Discontinued: Flowise (acquired by Workday, Aug 2025) was sunset in 2026 — code freeze 2026-07-29, GitHub repo archived 2026-08-13, end of life 2026-08-31. Was a visual LangChain canvas with LangChain-native memory nodes (Buffer, Buffer Window, Conversation Summary Buffer) backed by an internal chat_message DB table; Buffer Window kept the last K interactions, Summary Buffer compressed older turns while keeping recent ones verbatim.

  • LangGraph Persistence T2

    Distinct from LangMem. Built-in checkpointer saves graph state per super-step (short-term, thread-scoped). Store System adds long-term hierarchical key-value memory across threads with optional vector search + TTL. Postgres / Mongo / Redis stores for production.

  • AutoGen Memory T2

    AutoGen's memory layer: ListMemory chronological context plus teachable agents that vectorise corrections; integrates with Mem0/Zep rather than building deep memory natively. Microsoft AutoGen is in maintenance mode (community managed, bug and security fixes only), and Microsoft points new projects to Microsoft Agent Framework.

  • CrewAI Memory T2

    Memory subsystem inside the CrewAI orchestration framework; integrates with Mem0 for the long-term tier.

  • Hermes Agent memory (Nous Research) T3

    Nous Research's open-source self-improving agent keeps an agent-curated MEMORY.md/USER.md notebook injected at session start, full-text (FTS5) search over past sessions that returns raw messages without LLM summarisation, and optional Honcho user modelling. one of the most-starred agent projects of 2026.

Sources (42 cited facts, 4 third-party)

Each fact links to the page it came from; the badge says who published it (how to read sources).

What changed

Changes to this record's lifecycle, licence, release, pricing and hosting facts, from the catalog's git history. Subscribe (Atom)

  1. 2026-10-23
    • Compliance “Enterprise: SSO via SAML, RBAC, audit logs, multi-org management; data stays within region (multi-region support on…” → “Enterprise: SSO via SAML, RBAC, audit logs, multi-org management” source
    #223
  2. 2026-10-22
    • Pricing “Free 200 actions/mo; Pro $19/mo; Team $234/mo; Business/Enterprise: 2 credits per run (vs 4 for free). Actions + Ve…” → “Public pricing page now lists only Enterprise (custom actions/vendor credits; contact sales)” source
    • MCP support first recorded as “yes — hosted MCP server at mcp.relevanceai.com exposing agents/tools/knowledge to Claude, ChatGPT, Cursor etc. (OAuth, role-scoped); MCP client for external servers also documented” source
    #219