Blog
What we have learned building automation into working businesses — the parts that hold up, the parts that quietly fail, and how to tell them apart before you build.
Less than most people expect, and different from what they prepare. What is genuinely useful to bring to a first conversation — and what to leave at home.
· 6 min read
ReadOne of the most commercially valuable workflows to automate, broken down step by step — including the two places it usually goes wrong.
· 8 min read
ReadYes, to some of them, and the interesting question is which. A way of splitting an inbox that keeps the speed without risking the relationship.
· 7 min read
ReadA method you can apply before speaking to a supplier, including the two costs most business cases leave out and the one benefit most of them overstate.
· 7 min read
ReadAI is the more expensive, less predictable option and it is often the wrong one. A practical test for deciding which of the two a step actually needs.
· 7 min read
ReadNobody publishes a price list because the answer depends on the process. What actually drives the number, and how to estimate your own.
· 8 min read
ReadHuman-in-the-loop is easy to claim and easy to get wrong. What meaningful oversight looks like when the automation is running every day.
· 7 min read
ReadNo slides and no technology decisions. A walk through what happens in the first session, what you need to bring, and what you leave with.
· 5 min read
ReadNot every step in a workflow is a good candidate. A practical way to sort the steps worth automating from the ones that should stay human.
· 6 min read
ReadCoverage
Independent writing on Edugrade AI from the sector — Jisc, Advance HE and Queen Mary University of London. These are their words, not ours, and each link opens on their site.
Published under the product's earlier name, EduMark AI.
Jisc · National Centre for AI
An account of the marking and feedback tool and the work behind it at London South Bank University.
Advance HE
How the tool approaches assessment and feedback, and the ethical questions that shaped it.
Queen Mary University of London · Centre for Excellence in AI in Education
On aligning generated feedback to the rubric so it arrives while it is still useful to the student.
Queen Mary University of London · Centre for Excellence in AI in Education
On the difference between a mark and useful feedback, and why the educator has to stay in the loop.
In a free 30-minute discovery call we will look at how it works today, where the manual effort sits, what is worth automating, what is not, and where people should stay in the loop. No technical brief, no budget, no obligation.
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Tell me what your team still does by hand and I will sketch what automating it would look like.
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