MemClaw
The shared cognition layer for enterprise AI agents with governed access and cross-fleet memory
Enterprise
Focus
eToro
Production Customer
23ms
p50 Search
Overview
MemClaw is the shared cognition layer for enterprise AI agent fleets, enabling secure knowledge sharing across teams while maintaining governance controls. Unlike personal memory solutions, MemClaw is built for multi-agent, multi-fleet architectures with built-in permissions, audit trails, and tenant isolation. It features hybrid search (vector + keyword + graph), automatic entity extraction, contradiction detection via RDF triples and LLM analysis, and an 8-status memory lifecycle. Agents improve through interaction feedback, and the LLM-powered crystallizer automatically consolidates duplicate knowledge.
The Verdict
Who Should Use MemClaw?
Best For
- Enterprise teams running multi-agent systems
- Organizations needing governed knowledge sharing
- Teams requiring audit trails and compliance
- Multi-tenant AI deployments
- Agent fleets that need to learn from each other
Not Ideal For
- Single-agent personal assistants
- Teams wanting self-hosted/open source
- Budget-constrained startups
- Simple chatbot memory needs
What's Great
- Multi-agent, multi-fleet shared memory architecture
- Built-in governance: permissions, audit trails, tenant isolation
- Contradiction detection via RDF triples + LLM
- Knowledge graph with auto-extracted entities
- Hybrid search (vector + keyword + graph)
- Per-agent retrieval tuning and self-learning
- LLM-powered deduplication (crystallizer)
- Production-proven at scale (eToro: 21K+ memories, 23ms p50)
Watch Out For
- No self-hosted or open-source option
- Business tier ($399/mo) needed for larger deployments
- Free tier limited to 500 recalls/month
- Enterprise focus may be overkill for small teams
- Relatively new in market vs established alternatives
Pricing
Free
$0
10K memories, 500 recalls/mo, community support
Pro
$49/mo
250K memories, 3K recalls/mo, LLM enrichment
Business
$399/mo
1M memories, 10K recalls/mo, dedicated support + SLA
Custom
Contact
On-premises, air-gapped, white-label options
View all features & details
Core Features
- Multi-agent shared memory
- Cross-fleet recall
- Knowledge graph with entities
- Contradiction detection (RDF + LLM)
- 8-status memory lifecycle
- LLM crystallizer for deduplication
- Per-agent retrieval tuning
- Self-learning from feedback
Enterprise Features
- Permissions and RBAC
- Audit trails
- Tenant isolation
- Multi-fleet architecture
- Unlimited agents on all plans
Search Capabilities
- Vector similarity search
- Keyword/BM25 search
- Graph traversal
- Hybrid ranking
- 23ms p50 latency (production)
Use Cases
- Enterprise agent fleets
- Multi-team AI deployments
- Compliance-heavy industries
- Customer support agent networks
- Internal knowledge assistants
Real-World Usage
eToro Deployment
- 21,500+ memories stored
- 1,372 skills indexed
- 291 agent identifiers
- 23ms p50 search latency
How It Compares
| Feature | MemClaw | Mem0 | GBrain |
|---|---|---|---|
| Focus | Enterprise multi-agent | Personal/app memory | Personal knowledge synthesis |
| Governance | Built-in (RBAC, audit) | Basic | None |
| Multi-Fleet | Yes | No | Multi-brain federation |
| Contradiction Detection | Yes (RDF + LLM) | No | No |
| Self-Hosted | No | Yes | Yes |
| Open Source | No | Yes | Yes |
| Free Tier | Yes (limited) | Yes | N/A (OSS) |
| Best For | Enterprise agent fleets | Personalized AI assistants | Knowledge synthesis |
User Reviews
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