AI & Automation
AI & Automation · Capability

Document intelligence

Invoices, statements and forms read by machine and posted for review — capture clerks become reviewers instead of typists.

Reading a scanned invoice used to mean a clerk retyping it. Document intelligence platforms, most commonly built on services like Azure AI Document Intelligence, use OCR combined with a trained understanding of document structure to tell a line-item description from a vendor name from a total due, even across scans, photos and PDFs from vendors your system has never seen before. The output is structured data, not a wall of text, which is what actually lets it post into an ERP.

The realistic use case is a human-in-the-loop, not a human-out-of-the-loop: the model extracts and proposes, a person reviews the fields it wasn't confident about and approves the rest. That shift changes what a capture clerk's day looks like, from typing every field on every document to checking the exceptions a machine flagged. It's a meaningful productivity gain, but it depends on clean source documents and a review step that actually happens, not on the model getting it right unsupervised.

Part of AI & Automation

Approvals that chase themselves, documents that capture their own data, processes that run without being pushed. We automate the repetitive work inside and around your business systems — workflow automation first, and AI where it genuinely earns its keep.

Also part of AI & Automation
Questions we hear about AI & Automation
Which processes should we automate first?

Score your candidates by hours consumed per month, then automate the high-volume, rule-based, low-exception work first — invoice capture, order entry, follow-up emails, report generation. The classic mistake is automating the most visible process instead of the one quietly bleeding the most hours. Start with one, measure the return, then expand.

Are AI chatbots accurate enough to put in front of customers?

Only if they are designed not to guess. The cautionary tale is real — a tribunal held an airline liable for a refund policy its chatbot invented, because the bot speaks for the company. The discipline that works: ground the agent on your own approved content, constrain its scope, and hand anything binding — prices, commitments — to a human. That is exactly how we build ours.

Will AI replace our staff?

The evidence says AI reshapes more jobs than it replaces — and surveys of small businesses using AI show most grew headcount. In practice it removes the repetitive work from existing roles so the same team handles more volume, which matters most where skilled staff are scarce, as they are here. How leadership frames it decides whether the team embraces it.

What does automation cost, and what return should we expect?

Cost is driven by how many systems must connect, how many exceptions the process has, and the licensing of the tools involved — integration is often the largest slice. A well-scoped project typically shows measurable return within a year, judged against the hours it removes. We quantify those hours first, so the business case exists before the build does.

Platforms: Acumatica · Microsoft 365 · Microsoft 365 Copilot · 4flow · 4sign · Power BI · Custom APIs