KitchenAI
Simplify deploying AI frameworks into production applications
Overview
KitchenAI helps teams manage AI workflows like Langchain and RAG through a unified control plane. It lets developers deploy AI implementations as modular 'bento boxes' while maintaining version control and monitoring. Bridges the gap between AI specialists building models and application developers integrating them.
Key Features
Bento Boxes
Package AI workflows as versioned, self-contained modules
Unified API
Single endpoint for multiple AI frameworks/models
Framework Agnostic
Works with Langchain, LlamaIndex, OpenAI, and others
Real-Time Monitoring
Watch executions and debug workflows live
Version Rollbacks
Instantly revert problematic AI implementations
Use Cases
Integrate AI into existing applications
Build RAG-based AI workflows
Manage multiple LLM frameworks simultaneously
Pros & Cons
Pros
- Modular architecture prevents system-wide failures
- No vendor lock-in for AI frameworks/models
- Simplifies collaboration between devs and AI teams
- Production-ready monitoring and version control
Cons
Pricing Plans
Managed Cloud
Features
- 500 free AI credits for early adopters
- Scalable infrastructure
- Enterprise-grade reliability
Pricing may have changed
For the most up-to-date pricing information, please visit the official website.
Visit websiteFrequently Asked Questions
Can I use existing Langchain implementations with KitchenAI?
Yes, KitchenAI is framework-agnostic and works with Langchain, LlamaIndex, and other AI frameworks
How does version control work for AI implementations?
Bento boxes allow versioning and instant rollbacks of AI workflows
Is there a local development setup?
Yes, KitchenAI is open-source and can be self-hosted
Integrations
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