Each engagement produces a concrete deliverable: a plan, a supported interface, or a shipped system. AI is integrated where it creates business value and kept out of the paths that must stay deterministic.
| 01 | AI Architecture Review | Review an existing application and produce a practical integration plan: where AI should live, what data and tools it needs, how permissions should work, and what should remain deterministic. Deliverable: an integration plan with architecture drawings, tool and data inventory, permission model, and sequencing. |
| 02 | MCP & Agent Enablement | Expose an application's domain through MCP and/or application-native tools so Claude and other assistants can interact with business data through supported, permission-aware interfaces. Deliverable: an MCP server and/or Web MCP tool set over your domain, scoped to your permission model, with tests and documentation. |
| 03 | AI-Enabled Product Build | Design and deliver production web/mobile/business applications with AI capabilities integrated into the domain, workflows, tools, permissions, and audit model. Deliverable: a production system on the architecture behind Expense Organizer, handed over with the repository and the reasoning. |
Domain model, boundaries, permissions and audit before a line of code. AI features that cannot be audited are not features.
An MCP layer over your domain, so Claude and other assistants read, reason and act through the same rules your UI obeys.
Your repository, your infrastructure, your team on the tools. We stay as long as that takes and no longer.
Forty-five minutes. We look at the application you have and tell you where AI belongs in it, what it needs, and what should stay deterministic.