Seven examples of repeat work we automate: what we built, what it saved and which kinds of companies it fits. Where we have a real result, we show the number. Where we don't, we say so.
Book a free callClient names stay private, so each project is described by its industry. The numbers are real.
Store data, sales data and other sources are collected and prepared automatically, turned into a report and delivered to the inbox.
An AI assistant looks through old risk registers, finds similar risks and drafts a new register. The risk manager checks it before it is used.
An AI assistant inside the company's own Microsoft Azure environment drafts LinkedIn posts from project documents, in the company's tone. The team approves every post before it goes out.
Social media dashboards bring the numbers from every platform together on one screen. An AI strategist shows what works, why, and the next action for each episode.
One real project without a time-saving number, and two typical examples we have not published a client result for yet.
Models trained on existing geotechnical data predict soil properties in the design phase, before any lab test is run.
Your tools talk to each other. A new order, lead or file moves to the right place on its own, so nobody retypes it.
An assistant reads your company files and answers questions, with a link to the source.
Ask these five questions about a task. As a rule of thumb, if you answer yes to three or more, it is probably worth a call.
Work that changes every time, needs judgement about people, or happens only a few times a year is usually not worth automating. We tell you honestly when software or a simple fix is enough.
Book a free 30-minute call. We look at your process and tell you what is worth automating.
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