MemoryAtlas

Production polish: sub-300ms, SOC2/HIPAA, connectors, context fencing via container tags. Writes auto-extract facts into dual-layer user profiles (static + dynamic) and a unified knowledge graph; an asynchronous background pass ('Dynamic Dreaming', shipped May 2026) reconsolidates fragmented memories, reweights contradictions, and infers cross-memory connections without blocking the write path. Claims #1 on LongMemEval/LoCoMo/ConvoMem (self-reported); publishes an open-source benchmarking harness, MemoryBench, that others can run against Mem0 and Zep, though Supermemory's own headline numbers still come from its own runs of it.

Deep diveSupermemory deep dive: how the automatic memory API differs from Mem0 in practiceRead →
Storage
Cloud API, or local binary (full Memory API on localhost via one-command installer, embedded graph engine + local embeddings, BYO model incl. fully offline via Ollama)
Retrieval
Managed semantic retrieval with 'context fencing' (container-tag isolation) to keep tenants' memories from polluting each other; hybrid search combines RAG + memory in a single query; one call (~50ms claimed) returns both the ranked profile summary and relevant memories.
Self-host
Self-host: trivial
License
MIT
Pricing
Free ($5/mo incl.) → $19 → $100 → $399 → Enterprise, plus unit-based 'Context Cloud' usage pricing under the included credits (Memory $0.005/1K tokens, SuperRAG $0.001/1K, Search $0.005/1K queries, Operations $0.10/1K) · Freemium
GitHub stars
28,842
Last release
2026-07-19
Last commit
2026-08-10
First catalogued
2026-06-28

Strengths

  • Anti-pollution context fencing via container tags
  • Sub-300ms
  • Multi-tenant
  • Local binary self-host option (one command, zero config)
  • Connectors: Google Drive, Gmail, Notion, OneDrive, GitHub
  • Hybrid search: RAG + memory in one query
  • Asynchronous consolidation ('Dynamic Dreaming', May 2026): reconciles contradictions and infers cross-memory connections in the background without blocking writes
  • Automatic ingestion model: no manual add()-style memory calls, chunking strategy, or vector DB config required
  • Broad framework-adapter surface (Vercel AI SDK, LangChain, LangGraph, Mastra, Agno, CrewAI, Microsoft Agent Framework, Convex, VoltAgent, n8n, Zapier) plus coding-agent plugins for Claude Code, OpenCode, OpenAI Codex CLI, OpenClaw, and Hermes
  • Self-hosted local binary now supports pluggable embeddings (local ONNX default, or OpenAI/Google/Ollama) as of server-v0.0.5 (Jul 2026), narrowing the self-host/cloud capability gap

Watch out

  • Benchmark claims (#1 LongMemEval/LoCoMo/ConvoMem; SMFS's 55%-cheaper/more-accurate retrieval claim) are self-reported; no independent reproductions on file. Numbers also vary by page and methodology within Supermemory's own materials — its technical report claims 81.6% (GPT-4o) / 84.6% (GPT-5) / 85.2% (Gemini-3 Pro) LongMemEval accuracy via its own MemoryBench harness, while its research page separately claims 95% Recall@15 with aggregation (a different metric) — read any single number against its stated config, not as one settled score. A December 2025 Hindsight paper (arXiv:2512.12818) reprints these same Supermemory-reported figures rather than independently re-running them, and Mem0's own vendor comparison page pits its self-reported 94.4 against Supermemory's self-reported 85.2 as if the two were run under one shared methodology — they weren't
  • Automatic, profile-driven extraction trades off the fine-grained manual control that explicit-add frameworks like Mem0 offer; an April 2026 community comparison flagged the lack of first-class consolidation/contradiction-detection prior to Dynamic Dreaming shipping
  • SOC 2 + HIPAA BAA require Scale plan ($399+/mo) or Enterprise — lower tiers (Free, Pro, Max) do not include formal compliance certifications
  • Full cloud API self-hosting also gated to Scale/Enterprise; local binary may lack multi-tenant features
  • Proprietary internals on the cloud tier

Best for

  • Polished managed memory API with SOC 2 / HIPAA compliance
  • Coding-agent memory via MCP (Claude Code, OpenCode, OpenAI Codex CLI plugins)
  • One API over mixed data (files, email, PDFs, chat)

How it integrates

Benchmark results

No sourced results yet.

Sources

Last verified 2026-08-01 · updated by refresh-framework-cards