I will build autonomous multi agent system with langgraph or crewai


Level 1
Über diesen Service
Single-prompt AI chatbots fail when tasked with multi-step business logic. When you need automated research, data verification, code execution, or complex content operations, you need a team of specialized AI agents working in coordination.
I engineer autonomous multi-agent systems and agentic workflows using LangGraph, CrewAI, and Python. I build goal-driven AI teams where each agent has a distinct persona, memory, specialized tool access, and supervisor validation to deliver flawless results.
What You Get:
- Stateful multi-agent graphs using LangGraph or structured swarms using CrewAI
- Custom tool definitions (database queries, web scraping, CRM actions, API calls)
- Persistent memory and context retention across complex multi-step tasks
- Human-in-the-loop review checkpoints for critical business actions
- Production deployment as a standalone microservice or FastAPI backend
Replace manual workflows with an autonomous AI team that operates 24/7.
Send me a message outlining your desired workflow, and let us build your multi-agent system.
Lerne S M Russel kennen
AI Engineer and FullStack Developer
Level 1
- AusBangladesch
- Mitglied seitJuni 2024
- ⌀ Antwortzeit1 Stunde
- Letzte Lieferung4 Monate
Sprachen
Englisch, Bengalisch
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FAQ
What is the main difference between LangGraph and CrewAI?
CrewAI is ideal for role-playing collaborative teams and sequential workflows. LangGraph offers low-level cyclic graph control, conditional branching, and enterprise-grade state persistence. I will recommend the ideal framework for your use case.
How do you prevent agents from hallucinating or entering infinite loops?
I implement strict cyclic guardrails, execution step limits, and supervisor review nodes that validate every agent output before advancing state.
Can these agents interact with private company databases?
Yes. Agents can execute secure SQL queries, vector searches, and API calls using strict credential management.
