You don't need a chatbot. You need AI in your systems. You don't need a chatbot. You need the AI wired into the systems that run the work.

A chat box is a conversation. An integration is a worker. Bolting a chatbot onto your website gives customers something to type at; it doesn't touch the systems where your work actually happens. What we build reads your real data (an intake form, a remittance file, a 40-page submission), does something with it, and writes the result back into your CRM, ERP, or queue, with a person reviewing the calls that matter. If all you want is a smarter FAQ widget, we'll tell you, and you don't need us for that.

Whenever the work is deterministic. If a rule can be written down (a tax code, a routing table, a matching key), code runs it faster, cheaper, and exactly the same way every time. Handing that to a language model adds cost, latency, and a small chance of a confident wrong answer. We reach for AI where the input is genuinely messy or unstructured: reading a scanned document, classifying free text, drafting from context. Everywhere else, plain engineering wins, and we'll say so before you spend on a model that isn't earning its keep.

For a defined build it's a fixed quote, given after the free intro call and locked before we start. We don't publish a number because scope drives it: reading one document type is not the same as a full intake-and-routing pipeline. Ongoing support runs as a retainer sized to your operation. When a flat rate doesn't make sense, a scope still being discovered or a new document format nobody has modeled yet, we work hourly against a cap you set and convert to a fixed quote once it's pinned down. You'll also get a clear read on the running cost, the per-document model spend, before you commit, so there's no surprise on the monthly bill either.

Three ways. We constrain it to your actual data instead of its training memory, so it's reading your records, not guessing. We add review gates on anything consequential, low-confidence results and high-stakes calls route to a person before they're acted on. And we log every decision so there's an audit trail. The goal isn't a model you blindly trust; it's a pipeline where the routine flows through and the human sees exactly the cases that need judgment.

No. We build to your compliance requirements and put it in writing: your data stays in your systems, and nothing we build trains on it. Every engineer is a US citizen working in the US, so nothing leaves the country. We've shipped inside a Fortune 500 healthcare company and implemented PCI-DSS and KYC/AML programs, so regulated, sensitive data is familiar ground.