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Union.ai vs LangGraph

Union.aiLangGraph

Bottom line: Union.ai for mL engineers; LangGraph for engineering teams building production agents.

Union.aiUnion.ai

Durable AI and ML orchestration built on Flyte 2

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LangGraphLangGraph

Graph-based orchestration for stateful, controllable LLM agents.

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Votes00
PricingFreemiumFreemium
CategoryMlopsAgent Frameworks
Tags
mlopsorchestrationflyteworkflowsdurable-runtime
agentsorchestrationllm-frameworkopen-sourceworkflow
Best for
  • ML engineers
  • Data platform teams
  • Production ML orgs
  • Engineering teams building production agents
  • Developers needing controllable, resumable workflows
  • Teams already invested in LangChain
Pros
  • Built on proven open-source Flyte
  • Flyte 2 durable, infrastructure-aware runtime
  • Author workflows in pure Python, no new DSL
  • Automatic recovery from failures
  • Enterprise features: observability, SSO, RBAC
  • Explicit, debuggable control over agent state and flow
  • MIT-licensed core, free to self-host
  • Model-agnostic, not tied to one LLM vendor
  • Strong support for cycles, checkpointing, and human-in-the-loop
  • Backed by the widely used LangChain ecosystem
Cons
  • Python-centric workflow authoring
  • Orchestration concepts have a learning curve
  • Enterprise features are paid
  • Kubernetes knowledge helps for self-hosting
  • Overkill for very simple pipelines
  • Steeper learning curve than high-level agent builders
  • Requires comfort with graph and state concepts
  • Paid platform and observability are separate products
  • Documentation and APIs have evolved quickly
  • Can be overkill for simple single-shot LLM tasks

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