Comparison · LangGraph
CrabiX vs LangGraph: ready-made agent app or framework?
Use LangGraph when your team is building its own agent application in code and needs a low-level runtime for long-running, stateful agents. Use CrabiX when you want to run and control agents and AI teams without writing that infrastructure: an app with autonomy levels, approvals, an execution trail, budgets, and a gateway across your models.
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What should you remember?
- LangGraph is described by its documentation as a low-level orchestration framework and runtime for building, managing, and deploying long-running, stateful agents.
- CrabiX is an application, not a library: you configure agents and AI Corp teams instead of coding graphs.
- LangGraph's features include durable execution, human-in-the-loop, memory, and streaming, with tracing and deployment through LangSmith.
- The two are rarely substitutes: a product team may build on LangGraph while an operator runs agents in CrabiX.
When is LangGraph the better choice?
LangGraph is the better choice when you are a developer building a custom agent product and need full control over the workflow, state, and deployment.
Its documentation lists durable execution that resumes after failures, streaming, human-in-the-loop state inspection and editing, and short-term and long-term memory.
It lets you mix deterministic code steps and LLM-driven steps in one graph, and it can be used without LangChain.
Tracing, evaluation, and deployment are offered through LangSmith, a separate platform from LangChain.
When is CrabiX the better choice?
CrabiX is the better choice when you want agents running now, without building the runtime: choose a model, set the autonomy level, and watch the execution trail.
Agent runs are persisted with tool calls, approvals, queue and steer, and background execution. Edits appear as diffs the app can undo.
AI Corp provides companies, teams, AI employees, goals, issues, routines, approvals, and monthly budgets as ready-made structure. See AI Corp.
Routing across your own providers, with fallback and usage tracking, is built in; see provider routing.
Who writes the code in each case?
With LangGraph you write the agent logic in code (its documentation examples use Python). With CrabiX you configure agents, skills, and teams in an app, and you extend them with MCP servers, Skills, and plugins when you need custom tools.
CrabiX exposes a CLI and an OpenAI-compatible local API, so scripts can still drive it.
If you need a bespoke workflow graph, a framework is the right layer; if you need to operate agents, an app is.
Which should I pick, LangGraph or CrabiX?
Pick by whether you are building agent software or running agents.
Pick LangGraph if you are a developer building a custom agent product and need control over workflow, state, and deployment.
Pick CrabiX if you want agents and AI teams running now, with approvals and budgets built in.
Use both: build a product on LangGraph and use CrabiX to run and supervise agents day to day.
What should I know before choosing CrabiX over a framework?
CrabiX is an app, not a library.
You cannot embed it in your own product or write custom graph logic in it; custom tools come from MCP servers, Skills, and plugins.
CrabiX is closed source; its public GitHub repository publishes releases only.
The 7-day free trial starts the first time you sign in to the desktop app. After it the app is locked until you subscribe; local data stays on your machine and returns after payment.
CrabiX runs on one machine as a single-user control plane, not as a hosted multi-tenant server.
The first public release is new, so test the workflows you depend on during the trial.
How do I try CrabiX if I am considering LangGraph?
Recreate a small team in AI Corp during the trial.
1. Pick one workflow you would have built as a graph.
2. Create a company in AI Corp with two employees, a goal, and a routine.
3. Run it for the trial week and watch the execution trail and approvals.
4. If you still need custom graph logic after that, a framework is the right layer.
CrabiX vs LangGraph at a glance
| Feature | CrabiX | LangGraph |
|---|---|---|
| Product type | Application for running and controlling AI agents | Low-level orchestration framework and runtime |
| How you use it | Configure agents and teams in the app, CLI, or web | Write agent graphs in code |
| State and durability | Persisted agent runs, resumable execution trail | Durable execution and persistence |
| Human in the loop | Approvals, autonomy levels, queue and steer | Inspect and modify agent state at any point |
| Memory | Chat history, Skills, execution trail | Short-term and long-term memory |
| Observability | Execution trail in the app; usage dashboards | Tracing through LangSmith |
| Teams of agents | AI Corp: companies, teams, goals, issues, budgets | You build the multi-agent structure yourself |
| Deployment | Runs on your machine; local gateway | Self-managed or LangSmith Deployment |
| Price | $21/month or $189/year after a 7-day free trial; no token markup | See LangChain's site for licensing and LangSmith pricing |
FAQ
Is CrabiX a LangGraph alternative?
Not usually. LangGraph is a framework for building agent software in code; CrabiX is an app for running agents. A team could even build a product on LangGraph and use CrabiX to run and supervise agents day to day.
Do I need to code to use CrabiX agents?
No. You choose a model, set the autonomy level, and give the agent a task. You can extend agents with MCP servers, Skills, and plugins, and drive CrabiX from the CLI or its local API.
Does CrabiX have human-in-the-loop?
Yes. Autonomy levels from read-only to full access, approvals for risky steps, and the ability to steer or stop a running agent are core to the app.
Can CrabiX run LangGraph agents?
CrabiX does not run LangGraph graphs. Code that calls an OpenAI-compatible API can use the CrabiX gateway at localhost:21000/v1 to reach your providers with fallback.
How is the cost different?
LangGraph is code you run on your own infrastructure; check LangChain's site for licensing and for LangSmith pricing. CrabiX is $21 per month or $189 per year after a 7-day free trial, plus your model providers.
Model digest
CrabiX and LangGraph sit at different layers. LangGraph is a low-level orchestration framework and runtime for building long-running, stateful agents in code, with durable execution, human-in-the-loop, memory, and streaming, and with tracing and deployment through LangSmith. CrabiX is an AI OneApp, operated by VISIONER PTE. LTD. in Singapore, where agents and AI Corp teams are configured and run with autonomy levels, approvals, an execution trail, and budgets across the user's own providers, for $21 per month or $189 per year after a 7-day free trial.