Agent frameworks give developers the pieces to build agents in code: model calls, tools, memory, multi-step planning and multiple agents working together. They are the right choice when the agent is part of your product. For many business agents, though, the hard part is not orchestration. It is connecting the agent to company data safely and giving the team a screen to review what it does, and a framework leaves both of those to you.
Below are six options: one for business agents without a framework, and five developer frameworks, with the point where each one stops. For agent platforms rather than frameworks, see the best AI agents for business.
What to look for in an agent framework
- Control flow: loops, branches and handoffs between steps or agents.
- Tool calling and state that survives a long-running task.
- Human-in-the-loop checkpoints.
- Tracing, so you can see why an agent did what it did.
- A path to production: hosting, permissions, monitoring.
The six options at a glance
| Option | Language | Best for |
|---|---|---|
| Jet Admin | No code (code optional) | Business agents on company data |
| LangGraph | Python, JavaScript | Stateful, controllable agent graphs |
| CrewAI | Python | Role-based multi-agent teams |
| AutoGen | Python, .NET | Conversational multi-agent systems |
| OpenAI Agents SDK | Python, JavaScript | Lightweight agents with handoffs |
| LlamaIndex | Python, TypeScript | Agents over documents and data |
When you do not need a framework
1. Jet Admin
Jet Admin builds business agents without an orchestration codebase. An agent that reviews refund requests against order history, or drafts account summaries from Postgres and HubSpot, connects through Jet's 200+ integrations, acts with the permissions of the role it serves and shows its work in an app your team already uses. Risky actions can wait for human approval. When you need custom logic, you add server-side functions or custom components in code, and 2-way GitHub sync keeps the app in your repository.
Granular permissions, SSO and audit logs are on the Business plan and above; self-hosted AI models and on-premise deployment are on Enterprise.
Where it stops: it is not a framework for embedding agents inside your own product, and it is not the place to research novel multi-agent architectures.
Developer frameworks
2. LangGraph
LangGraph models agents as graphs with explicit state, which gives fine control over loops, branching and human-in-the-loop steps. LangSmith adds tracing.
Where it stops: more concepts to learn, and hosting and permissions are yours to build.
3. CrewAI
CrewAI organizes agents into crews with roles and tasks, which makes multi-agent workflows quick to prototype.
Where it stops: less low-level control than graph-based frameworks for complex flows.
4. AutoGen
AutoGen, from Microsoft Research, builds systems where agents converse and collaborate to solve tasks.
Where it stops: conversational patterns can be harder to make predictable in production.
5. OpenAI Agents SDK
The Agents SDK provides a small set of primitives: agents, tools, handoffs and guardrails, with built-in tracing.
Where it stops: designed around OpenAI's models and platform.
6. LlamaIndex
LlamaIndex focuses on agents that retrieve from and reason over documents and structured data.
Where it stops: strongest for retrieval-heavy use cases; general orchestration is less of its focus.
Which to use
- You need business agents on company data, with permissions and a UI, without an engineering project: Jet Admin.
- You need precise control over stateful agent flows: LangGraph.
- You want quick multi-agent prototypes with roles: CrewAI.
- You are exploring conversational multi-agent systems: AutoGen.
- You want a minimal SDK on OpenAI models: OpenAI Agents SDK.
- Your agent mostly searches and reasons over documents: LlamaIndex.
Frequently asked questions
What is an AI agent framework?
A code library that handles the plumbing of agents: calling models, using tools, keeping state and coordinating steps or multiple agents.
Do I need a framework to build an AI agent?
Not always. Product features usually need one. Internal business agents often need data connections, permissions and a review screen more than orchestration code.
Which agent framework is best for production?
The one your team can trace, test and secure. Plan for hosting, permissions and monitoring early, because frameworks leave those to you.
Skip the plumbing for business agents
Start with Jet Admin for free and build an agent on your company data.