Supermemory vs Zep

Detailed side-by-side comparison to help you choose the right tool

Supermemory

🔴Developer

AI Knowledge Tools

Supermemory is the memory and context layer for AI agents — a graph-based memory API with extractors, connectors, and retrieval for personal apps and enterprise stacks.

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Starting Price

Custom

Zep

🔴Developer

AI Knowledge Tools

Enterprise agent memory built on temporal Context Graphs (Graphiti) with millisecond retrieval, SOC 2 Type II, and HIPAA BAA.

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Starting Price

Free

Feature Comparison

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FeatureSupermemoryZep
CategoryAI Knowledge ToolsAI Knowledge Tools
Pricing Plans478 tiers408 tiers
Starting PriceFree
Key Features
  • Memory, RAG, and extraction through one API
  • Supermemory MCP for exposing memory to compatible tools
  • Connectors for Google Drive, Notion, and OneDrive on Pro
  • Temporal Knowledge Graph
  • Context Engineering
  • Graph RAG

💡 Our Take

Choose Supermemory if you need a complete memory graph (not just partial), consumer plugins, document extractors, and an open eval platform — capabilities Zep does not offer per Supermemory's own comparison. Choose Zep if you are already committed to its temporal knowledge graph approach and your use case is narrowly focused on conversational memory for chatbots.

Supermemory - Pros & Cons

Pros

  • Graph + extractor approach catches facts that vector RAG misses
  • Connector library means real productivity in days, not weeks
  • Free tier is generous enough to ship a hobby project end to end
  • Pro at $19/month is one of the cheapest production memory APIs
  • MemoryBench research signals the team is investing in evaluation rigor

Cons

  • Scale jumps from $19 to $399 — mid-volume teams have a steep step
  • Graph queries add latency vs raw vector lookups
  • Newer than Mem0/Zep, so ecosystem and community examples are smaller
  • Closed source on the platform side; self-host limited to enterprise
  • Connector reliability depends on third-party APIs (Slack, Notion, etc.)

Zep - Pros & Cons

Pros

  • Temporal knowledge graph captures when facts changed — better than "last-message wins" vector memory
  • ~200ms retrieval keeps memory viable in latency-sensitive agent flows
  • Credit-based pricing makes storage and retrieval free — predictable for read-heavy agents
  • SOC 2 Type II + HIPAA BAA + DPA make procurement realistic at regulated enterprises
  • First-class MCP server integrates with Claude Desktop, Cursor, and OpenAI Agents SDK out of the box

Cons

  • Credit math (1 credit per 350 bytes per Episode) is hard to forecast until you measure real payloads
  • Free tier (1,000 credits/mo, no rollover) is tight even for evaluation
  • Webhooks, analytics, and custom extraction live only on Flex Plus ($375/mo) and above
  • Most compliance value (audit retention, BYOK/BYOC) is gated behind Enterprise pricing
  • Temporal graph modeling adds upfront design work vs throwing chat history into a vector DB

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🔒 Security & Compliance Comparison

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Security FeatureSupermemoryZep
SOC2
GDPR
HIPAA
SSO
Self-Hosted
On-Prem✅ Yes
RBAC
Audit Log
Open Source
API Key Auth✅ Yes
Encryption at Rest✅ Yes
Encryption in Transit✅ Yes
Data Residencyconfigurable
Data Retentionconfigurable
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