Build an agent system you can run yourself.
An agent is a workflow in which a model uses tools to complete a task. Connect open models to your tools and data, with agreed permissions, human approvals and failure handling. Our engineers keep supporting the systems they build under agreed terms.
Who this is for
- You have a defined internal workflow or agent product to connect to real systems.
- You need control over the model deployment and how the workflow acts.
What you receive
- Integrations within the agreed workflow.
- Tool permissions, approval steps and failure handling.
- Tests built from representative examples.
- Deployment configuration and operating instructions.
How it runs
Map the decisions
Define inputs, actions, approvals and failure paths.
Build and test the workflow
Connect the chosen models and tools, then test the complete task.
Deploy with its operator
Install the system, document its operation and agree continuing support.
Measure the whole workflow
Retrieval, tool calls and approvals affect the result. Model generation speed alone does not describe how quickly the system finishes a task.
Scope, handover and support
Your proposal sets out the work, price, start and handover dates, and what is needed from you. Hardware, cloud charges, engineering and ongoing operation belong in the cost discussion. On-site days and continuing support are agreed as part of the engagement. Our engineers keep supporting the systems they build under those terms.
Questions about the work
How is the price decided?
From your workload, hardware and the implementation and support scope we agree together. Your proposal separates the engineering work from hardware, cloud and ongoing operating costs.
Who keeps supporting the system?
We agree support coverage, on-site work and how to handle problems before starting.
Do I need to buy hardware first?
No. Start with your workload and budget. We compare the options before recommending a purchase or deployment.