Supplier bills that read themselves
OCR and AI read purchase invoices; the team checks them side by side and exports accounting-ready files.
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We use AI where it saves real hours: reading documents, drafting listings and replies, summarising calls and turning data into plain-language reports — always with a person approving what matters. Our team has built 20+ AI-powered tools on OpenAI, Gemini and Claude.
Teams drowning in repetitive reading and writing: invoices, listings, support messages, call notes and reports. If a task is high-volume, rule-bound and checked by a person anyway, AI can usually do the first draft in seconds and leave your team the judgement calls.
Real systems our team has built. Client names stay private.
OCR and AI read purchase invoices; the team checks them side by side and exports accounting-ready files.
Drafts titles, meta descriptions, alt text and FAQ schema for weak products, and applies them after review.
Read-only MCP servers that let an AI assistant answer questions about orders and stock without anyone sharing passwords.
It can, which is why every workflow we build has a review step for anything that touches money, customers or published content, and a log of every change.
We use the AI providers' API services and send only the data each task needs. We'll walk you through each provider's data policy before you decide.
A Model Context Protocol server gives an AI assistant a defined, limited way to query your systems — for example read-only access to orders or stock — instead of handing it your passwords.
With one high-volume task that has a clear right answer — for example reading invoices or drafting listings. We measure the time it takes today, automate the first draft and keep a person approving the result.
Tell us what you're building. A real person from our team replies, usually within one working day.