Document processing, agents and copilots wired into your real workflows — scoped to one task, proven on your data, shipped on a fixed quote.
Your team pastes invoices, emails and PDFs into an AI chat, copies the answer back out, and hopes. Lunch breaks are spent in pilot purgatory — a demo here, a proof of concept there, and nothing connected to the systems where the work actually happens.
The gap was never the models. They are excellent. The gap is engineering: routing documents, validating output, handling the edge cases, and knowing when a human has to stay in the loop. That is exactly the job we show up for.
Invoices, forms, certificates and correspondence read automatically — extracted, validated and filed into your real systems.
Software that makes decisions across steps: routing, triaging, drafting and escalating — with an audit trail you can actually audit.
Guided assistance inside your own tools — drafting quotes or reports from your data, with a human approving every output.
The email-drives-everything shuffle replaced by defined, instrumented pipelines that touch your existing stack.
Structured data plucked from unstructured mess — hand-written notes, scanned PDFs, mixed formats.
Model selection, prompting and caching tuned to cost per document — because accuracy at any price is not a business model.
We start with one specific, measurable task — reading a document, processing an inbox, drafting a quote — and prove it on your real data with accuracy and cost-per-unit tracked from day one. Only when the numbers beat the manual process do we talk about scale.
If what you actually have is a manual typing problem, the honest advice may cost less than you think — see data entry automation before you pay for intelligence. And if the AI question is really “what would it take to build the underlying app properly”, custom software development is the better page for you. Either way, the call decides in 45 minutes.
First call is 45 minutes and genuinely useful, even if we do not work together.