Mnemo vs Competitors

Feature Comparison

Capability	Mem0 $249	Zep (usage)	Letta $20	Cognee OSS	Mnemo Core FREE	Mnemo Pro $69
Vector search	✅	✅	✅	✅	✅	✅
BM25 keyword search	❌	❌	❌	✅	✅	✅
Knowledge graph	$249/mo	✅	❌	✅	✅	✅
Forgetting model	❌	Basic	Basic	❌	Weibull	Weibull
Memory tiers	❌	❌	❌	❌	✅	✅
Cross-encoder rerank	❌	Basic	❌	❌	✅	✅
Contradiction detection	❌	✅	❌	Partial	✅	✅
Triple-path fusion	❌	❌	❌	❌	✅	✅
Scope isolation	Basic	❌	❌	❌	✅	✅
Multi-backend	20+	Neo4j only	Postgres	7+	4	4
Self-hosted	Hard	❌	Docker	✅	✅	✅
$0 local (Ollama)	❌	❌	❌	❌	✅	✅
TypeScript SDK	✅	✅	✅	Partial	✅	✅

Architecture Differences

Mem0

• Cloud-first SaaS with open-source self-hosted option
• Graph features locked behind $249/mo Pro tier
• 50k+ GitHub stars, largest community
• AWS exclusive memory partner

Zep

• Built around Graphiti temporal knowledge graph
• Usage-based pricing ($1.25/1K messages)
• Self-hosted Community Edition deprecated
• Requires Neo4j

Letta (formerly MemGPT)

• Full agent platform, not just memory
• Agents manage their own memory
• Requires running a Letta server
• Heavier adoption cost if you just need memory

Cognee

• Python-first knowledge engine
• Batch processing (cognify step)
• Best for document-heavy structured data
• TypeScript is secondary

Mnemo

• Cognitive science-first — Weibull decay, not just storage
• Lightweight — npm install, 4 lines to start, 142KB
• Fully local — Ollama + LanceDB, $0, no cloud
• Triple-path retrieval — Vector + BM25 + Graph fused with RRF
• Multi-backend — LanceDB, Qdrant, Chroma, PGVector

When to Choose Mnemo

• You want intelligent forgetting, not infinite storage
• You need a lightweight, embeddable memory layer (not a full agent platform)
• You want to run locally for free with Ollama
• You care about retrieval quality (triple-path + rerank + decay)
• You're building in TypeScript/Node.js