Agent ownership comparison
Agentlas vs Other AI SaaS
Other AI SaaS rents you a powerful seat. Agentlas helps you keep the worker itself: build or borrow an agent, run it with your chosen supported host, preserve the owned package in private Agent Cloud, and publish a separate copy to the Hub only when you decide.
The category line is ownership
Google, Cursor, and other AI workspaces
They compete for the seat, editor, workspace, and daily AI workflow. Agentlas competes for who owns the agent after that work is done.
OpenAI, Anthropic, Gemini, and supported hosts
They provide models and execution environments. Agentlas supplies the portable package, ownership boundary, routing, Cloud restore, and Hub access around them.
CrewAI, LangChain, and LangGraph
Useful code primitives for developers—but still code you integrate, host, secure, migrate, and maintain. A framework is not an owner trust, private vault, borrowing network, or asset economy.
Seat rental versus agent ownership
| Other AI SaaS | Agentlas | |
|---|---|---|
| What you pay for | Access to a vendor workspace, model, editor, or automation feature. | An Agent OS that treats the agent package itself as an owned, restorable asset. |
| What stays yours | Your inputs and outputs may be exportable; the configured worker usually remains tied to that product or company workspace. | The agent package keeps owner scope, origin, version, package identity, visibility, and restore history. |
| When you change tools | Rebuild the workflow in the next vendor, or keep paying for the workspace where it was created. | Restore the owned package on another supported host, then reconnect that computer's keys, files, tools, and permissions. |
| Model choice | Usually optimized around the vendor's own model or approved model menu. | Use a supported host and the model account or API key you choose. The host performs the work; Agent Cloud does not run the model. |
| Private vs public | Sharing, templates, and workspace storage commonly live inside one vendor boundary. | Owner-private Agent Cloud and public Hub are separate scopes. Saving privately never means publishing. |
| Build or borrow | Build inside the product, then keep the result in that product. | Build an owned agent, borrow a public Hub specialist, or form a temporary team without merging ownership scopes. |
| Creator economy | Most SaaS products charge for seats or usage; your configured worker is not a leasable asset. | A published Hub agent can earn Agentlas credits when other users borrow it. Credit rules are product terms, not a promise of cash value. |
| Execution boundary | Cloud execution follows the SaaS provider's infrastructure and permission model. | Execution happens in the supported host you select, using that environment's credentials, project context, files, tools, and approvals. |
Frameworks stop where ownership begins
CrewAI, LangChain, and LangGraph can help engineers assemble an agent application. They do not make the agent an independently owned product asset. There is no built-in Agent Trust record, owner-private Agent Cloud, public lease entitlement, cross-host restore receipt, or creator credit loop. They sell or provide building blocks. Agentlas operates the asset lifecycle.
Frequently asked questions
Is Agentlas another AI subscription?
It has plans and credits, but the product boundary is different. Agentlas is built around an owned agent package that can be kept private, restored, inspected, run through supported hosts, or deliberately published to the Hub.
Are Google and Cursor competitors?
Their workspace and coding-agent surfaces compete for where people do AI work. Agentlas competes by making the agent portable across supported environments instead of making one vendor workspace the permanent home of the worker.
Are OpenAI and Anthropic competitors or partners?
For Agentlas they are model and host ecosystems. Agentlas can use supported OpenAI- and Anthropic-powered hosts while keeping package ownership, Cloud scope, Hub entitlement, and local permissions in the Agentlas layer.
What about CrewAI, LangChain, or LangGraph?
They are code frameworks, not an Agent Trust or asset network. They provide primitives for developers to assemble and operate applications. They do not give the user an owner-scoped Agent Cloud, a public borrowing market, portable ownership receipts, or a creator credit economy. If you choose them, your team also owns the integration and operations burden.
Does portability move my API keys and company files?
No. That would be unsafe. The agent package can move; machine-local credentials, files, tool connections, and permission grants stay in each environment and must be connected again.
Does Agentlas promise cash income or a token?
No. Current Hub activity can accrue product credits under the published rules. Any future settlement or token experiment would require separate technical and legal review and is not promised in advance.
Keep the agent, not just the subscription.
Use Agentlas Desktop for local work, Agent Cloud for owner-private restore, and the Hub when you want to borrow or publish.