We have the answer.
( Questions? Answered )
How do we know if our workflow is AI-ready?+
We start with workflow discovery: mapping the process, decision points, exceptions and data. Mostly reading and answering → RAG. Needs decisions and actions → an agent. You get that read on the first call.
Will you train on or expose our data?+
No. We prototype on synthetic data and only swap in real integrations once behavior is proven, within your security boundaries. Nothing trains external models, and every action is logged and auditable.
How long until something is in production?+
Technical proposal with architecture and timeline in 5 days; first production deploy in under 4 weeks for a scoped workflow. We ship the safest first workflow, then expand once it earns trust.
What does it cost?+
A digital worker runs 10–50× cheaper than a full-time hire, with predictable pricing. Fixed-price projects, monthly retainers or short advisory sprints — scoped up front, no open-ended billing, token budgeting baked in.
Who owns what we build?+
You do. Code, prompts, evals and infrastructure live in your repos and your cloud from day one. If we ever part ways, everything keeps running without us — no lock-in, no black boxes.
What happens after launch?+
Nothing ships without monitoring, approval gates for sensitive actions and rollback. After launch we stay on for support and iteration — retainer or ad-hoc — and you get full runbooks either way.