📖 The AI Tool Bible

Chassis vs LangGraph

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

 
Chassis
Agents
LangGraph
Agents
TaglineOpen-source tool that auto-packages ML models into production-ready Docker containers with a prediction API.Stateful, graph-based agent orchestration from LangChain.
CategoryAgentsAgents
PricingFree· Free, open source (Apache-style community project)Freemium· Free open-source; LangGraph Platform paid
Model—BYO (Claude / GPT / open)
Editorial score—8.8 / 10
Use cases
model-packagingedge-deploymentml-containerizationmlopskubernetes-serving
stateful agentshuman-in-loopproduction
Pros
  • One Python call turns a trained model into a Docker prediction container
  • Cross-compiles for x86 and ARM, including Jetson and Raspberry Pi
  • Framework-agnostic across Scikit-learn, PyTorch, TensorFlow
  • Fully open source with no vendor lock-in to Modzy
  • Reliable, debuggable agent graphs
  • Built-in persistence + HITL
  • Production-grade
  • Tight LangSmith integration
Cons
  • Not an AI model itself, just deployment glue
  • Release activity has slowed; community support is the main channel
  • Requires Docker installed locally and some wrapper code
  • Steeper learning curve than CrewAI
  • Verbose to set up
Websitechassisml.iowww.langchain.com
Pick Chassis if
  • ✅ One Python call turns a trained model into a Docker prediction container
  • ✅ Cross-compiles for x86 and ARM, including Jetson and Raspberry Pi
  • ✅ Framework-agnostic across Scikit-learn, PyTorch, TensorFlow
  • ✅ Fully open source with no vendor lock-in to Modzy
Pick LangGraph if
  • ✅ Reliable, debuggable agent graphs
  • ✅ Built-in persistence + HITL
  • ✅ Production-grade
  • ✅ Tight LangSmith integration
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