Built for real work,
built to be trusted.
Explore architecture options for a custom project. Exact controls and responsibilities are agreed before implementation.
I build AI systems around your workflow, with hosting, data boundaries, and access controls chosen for your project.
The runtime should fit the job. We can use a dedicated machine, a sandbox, or managed services depending on the workload.
Isolation requirements are assessed alongside cost, deployment, and maintenance needs.
Credentials belong in an appropriate secrets store, with only the access each integration needs.
A real browser,
in every sandbox.
Access and session handling need explicit boundaries, especially when a browser can act on an account.
The integration layer connects the approved providers and records useful usage information.
Connect the APIs your workflow needs.
Memory should help the workflow without collecting more information than it needs. We define what is retained and how it can be reviewed.
Useful context, with clear controls.
A custom system can combine interfaces, background jobs, and integrations around the way your team works.
Build for the way your team works.
Illustrative architecture comparison. Check each provider’s current documentation for its own features.
Illustrative architecture comparison. Actual capabilities and controls depend on the product and configuration.