All Stacks
Multi-Agent AI
Multi-Agent Developer Stack
Build production multi-agent systems with the tools that cover orchestration, observability, model access, and visual flow building, end to end.
Our Take
This is a stack for developers building systems where multiple AI agents coordinate on a task, not a single chatbot with tools. CrewAI and AutoGen both orchestrate multi-agent workflows, the real difference is CrewAI's role-based structure versus AutoGen's more flexible conversation-driven pattern, pick based on how rigidly defined your agents' roles are. One thing to confirm before committing to AutoGen for a new build: Microsoft's original AutoGen repository is now in maintenance mode, folded into the newer Microsoft Agent Framework, with the community AG2 fork carrying active development forward, so check which lineage a tutorial or template is actually built on. Existing AutoGen installations keep running either way, this is a heads-up for new builds, not a reason to migrate off a working one. LangSmith is the piece worth taking seriously early, debugging a multi-agent system without observability into what each agent actually did gets painful fast.
True Cost & Exit
What this stack really costs to run, and how you'd leave it.
Monthly cost
from $74/mo fixed (LangSmith Plus + Flowise Starter), plus usage-based Replicate model-hosting costs that scale with compute and have no fixed floor
Lean alternative
CrewAI, free and open source, covers multi-agent orchestration on its own; add LangSmith once you need production observability into what each agent actually did, and treat Replicate's pay-as-you-go model hosting as scaling with usage, not a fixed cost to budget upfront.
Exit path
Agent definitions and orchestration logic live in your own CrewAI or AutoGen project code, not locked in a proprietary format, since both frameworks are open source; LangSmith's trace history is the one piece that doesn't travel with you if you switch observability tools, so archive traces you need to keep before migrating.
Tools in This Stack
Build and deploy collaborative multi-agent workflows with an open-source framework used by a large share of Fortune 500 companies, plus a paid cloud platform for execution hosting and monitoring.
Build LLM-based multi-agent systems with patterns like GroupChat. Microsoft's original AutoGen repo is now in maintenance mode and community-managed; Microsoft names its own Agent Framework as the enterprise-ready successor for new projects, with AG2 available separately as an independently-maintained community fork.
Debug, test, and monitor LLM applications and agents in production with LangChain's observability platform, billed by trace volume and seats.
Run and deploy machine learning models via API with per-second usage billing and no idle costs for public models.
Assemble chatbots and multi-agent workflows on a drag-and-drop canvas without writing backend code. Acquired by Workday in August 2025 and being integrated into their platform.