AI Copilot Development, Built Into Your Product

A chatbot is a conversation you go to; a copilot is help that comes to you. The copilot already knows the record you are on and what you are permitted to see, and it proposes actions you accept in place. Practically, the difference shows up in acceptance rate, copilots are used because they cost the user nothing to try.

Yes, we build in your components and design system rather than dropping in an iframe, which is what makes a copilot feel native. We need access to your context (current record, selection, user permissions) through your own state layer; if that is not exposed yet, surfacing it is usually a small piece of groundwork we scope up front.

We start with a short discovery call to clarify goals, constraints, and success metrics. Then we identify high-impact AI use cases, review your data and systems, and propose a phased roadmap with costs and risks attached to each phase.

Discovery runs 2 to 4 weeks, an MVP typically lands in 8 to 16 weeks of weekly-demo sprints, and operate is an ongoing arrangement with monitoring and support after launch.

Fixed-scope work is priced per milestone, dedicated teams are billed monthly per seat, and staff augmentation is weekly or monthly. You pick the model that fits and can switch between phases. There is a fuller breakdown of what moves the number on our AI development cost page.

You do. The full repository, documentation, and deployment transfer to you at every milestone, with no lock-in to us.

NDAs from day one, scoped access, and data residency decided at the architecture stage. We work within HIPAA, SOC 2, and similar requirements where they apply.

We monitor accuracy, cost, and uptime, run regression checks as models drift, and keep a defined escalation path with support so the system stays healthy after release.