Do we have to replace our software?
No. The architecture starts from the tools you already run. Agents get read and write access through your existing systems' APIs or middleware. If something has to change, it shows up in the audit as a cost, not as a surprise mid-build.
What does a feasibility audit cost, and how long does it take?
Fixed scope and a fixed price, agreed before anything starts. A single-workflow audit is measured in days, not months. You get the written verdict whether or not we build anything together.
Our data is a mess. Is that a dealbreaker?
It is the most common finding, and it is exactly what the data layout evaluation is for. The usual verdict is "fix these three things first," with the fixes listed. Automating on top of messy data is how hallucinated records happen, so we don't.
What stops the AI from doing something expensive or embarrassing?
Two layers. Deterministic filters catch anything that violates a rule you set (amounts, fields, formats, recipients). A human sign-off gate sits in front of the actions you define as consequential: anything that moves money, commits you to a customer, or sends something outside the company. Routine actions, like creating a record from validated fields, run inside the rules; exceptions and anything that fails validation go to a person. Nothing high-risk runs without approval.
Is a digital twin the same as a business simulator?
Same discipline, two time horizons. The twin asks whether an automation behaves correctly before it goes live. A decision simulator asks whether a pricing, staffing, or supplier change pays off before you commit. Both model your business as a connected system and run it against scenarios first.
Who actually does the work?
One accountable architect owns the engagement end to end. Build capacity comes from a vetted network of integration developers, data specialists, and QA, scaled to the scope of the job. You always know who is responsible.
