Zep
ExternalZep is a context engineering platform that intelligently assembles context from chat histories, business data, and user behaviors into a dynamic temporal knowledge graph for building personalized AI agents. It delivers ultra-fast retrieval under 200ms P95 with high accuracy on benchmarks like LoCoMo, while minimizing LLM costs through token-efficient context assembly. Ideal for developers and teams in sales, support, e-commerce, healthcare, and real-time voice/video applications needing reliable, evolving memory with enterprise compliance.
Description
Zep is a context engineering platform that intelligently assembles context from chat histories, business data, and user behaviors into a dynamic temporal knowledge graph for building personalized AI agents. It delivers ultra-fast retrieval under 200ms P95 with high accuracy on benchmarks like LoCoMo, while minimizing LLM costs through token-efficient context assembly. Ideal for developers and teams in sales, support, e-commerce, healthcare, and real-time voice/video applications needing reliable, evolving memory with enterprise compliance.
Key capabilities
- Assembles context from chat history, business data, and user behavior into unified temporal knowledge graph
- Supports ingestion of chat messages, JSON, and documents
- Builds evolving KG with automatic fact invalidation to prevent stale data
- Provides token-efficient, low-latency retrieval (P95 <200ms) formatted for LLMs
Core use cases
- 1.Personalized sales agents with CRM integration
- 2.Customer support with historical and business context
- 3.E-commerce personalization from user behavior
- 4.Healthcare applications with domain-specific entities
- 5.Real-time voice/video/live support agents
Is Zep Right for You?
Best for
- Developers building personalized, real-time AI agents
- Teams in sales, support, e-commerce, healthcare needing precise recall
- Applications requiring low-latency retrieval like voice/video support
Not ideal for
- Users needing simple static RAG or chat-only memory
- Teams lacking LLM structured output support or custom configuration expertise
Standout features
- Custom entity types and relationship models for domains like sales, support, healthcare
- Preformatted, customizable context templates
- Persistent context with provenance and temporal tracking
- Enterprise-grade: SOC 2 Type II, HIPAA compliant
- Developer-friendly integration in 3 lines of code
- Open-source Graphiti library
Pricing
Enterprise Plans
Flex Plus Plan
Free Plan
Flex Plan
Reviews
Based on 0 reviews across 0 platforms
User Feedback Highlights
Most Praised
- Smart automatic context unification from multiple sources
- Temporal knowledge tracking prevents outdated information
- Significantly reduces LLM token costs
- Highly customizable for specific industries
- Strong testimonials on game-changing impact
- Easy integration and popular open-source adoption (22k GitHub stars)
Common Complaints
- Benchmark performance claims had discrepancies (e.g., 84% to 75%)
- Scalability issues during 30x usage spikes causing failures
- Long ingestion times due to serial processing
- No support for Azure OpenAI or some smaller LLMs
- Compatibility and database/graph structure issues reported
- Requires domain-specific configuration effort