Join Date
August 2024
Country
Gender
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Age
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About Daniel Chalef
Co-founder of Zep AI
Companies & Work
![Zep AI](https://bookface-images.s3.amazonaws.com/small_logos/01c6d0585e8c71ae2a60d4a67e5c15a449165704.png)
Zep AI
Build AI assistants that continually learn and delight users with personalized and accurate experiences.
## Memory that learns from your users
Zep intelligently learns from user interactions, improving your assistant or agent's knowledge over time. Recall user facts in milliseconds, with Zep adding no latency to your prompt creation.
## Ready for Production and Scale
- Granular Memory Controls: Go beyond semantic search with developer-defined rubrics for user fact relevance.
- Comprehensive APIs and SDKs: Python, TypeScript, and Go SDKs, with full CRUD control of stored facts.
- SOC 2 and tools for Privacy Compliance.
## Build Consistent and Correct LLM Apps
Zep's Structured Output and Dialog Classification tools build on Zep's memory enabling you to build more accurate and consistent user experiences.
- Extract strongly-typed data from chat history, quickly & accurately: Go beyond your LLM provider's JSON or Structured Output mode with built-in types for datetimes, floats, emails, RegEx patterns, and more.
- Instantly classify conversation state: Understand user intent and emotion, segment users, and more.
## Memory that learns from your users
Zep intelligently learns from user interactions, improving your assistant or agent's knowledge over time. Recall user facts in milliseconds, with Zep adding no latency to your prompt creation.
## Ready for Production and Scale
- Granular Memory Controls: Go beyond semantic search with developer-defined rubrics for user fact relevance.
- Comprehensive APIs and SDKs: Python, TypeScript, and Go SDKs, with full CRUD control of stored facts.
- SOC 2 and tools for Privacy Compliance.
## Build Consistent and Correct LLM Apps
Zep's Structured Output and Dialog Classification tools build on Zep's memory enabling you to build more accurate and consistent user experiences.
- Extract strongly-typed data from chat history, quickly & accurately: Go beyond your LLM provider's JSON or Structured Output mode with built-in types for datetimes, floats, emails, RegEx patterns, and more.
- Instantly classify conversation state: Understand user intent and emotion, segment users, and more.