Both GPT-4o and Claude can look at an image of a document and tell you what it says — or answer questions about it, extract specific fields, summarise it, or analyse its content. For businesses building document processing workflows, the question is which one does it better and for what types of documents. The honest … Read more
Visual quality inspection has traditionally meant either a person looking at every item — slow and inconsistent — or expensive dedicated machine vision systems that require specialist integration. AI vision tools are opening a middle path: using models that can analyse product photos and flag defects, at a cost and complexity level that’s accessible to … Read more
Manual data entry from invoices and receipts is one of the most time-consuming and error-prone tasks in any accounts team. Someone photographs a receipt, types the vendor name, amount, date, and category into a spreadsheet or accounting system — then does it again for the next one, and the next. It’s repetitive, it scales with … Read more
Most people use AI by typing text and reading text back. But every major AI model — GPT-4o, Claude, Gemini — can also accept images as input. You can upload a photo, a screenshot, a document scan, or any other image, ask a question about it, and get a useful answer back. This capability is … Read more
If someone asked you right now how much your business spends on AI tools every month, could you answer confidently? Most people can’t — and that gap between “we pay for some AI stuff” and “here’s exactly what we spend and what we get for it” is where a surprising amount of money quietly disappears. … Read more
Every AI model launch comes with a table of impressive-looking scores. Claude scores X on MMLU. GPT-5 scores Y on HumanEval. The new Gemini model tops the LMSYS leaderboard. If you’re a business buyer — not a machine learning researcher — these numbers probably look a lot like car specs you don’t fully understand but … Read more
The question every team building with AI eventually asks is some version of this: “How do we know the model is doing a good job?” The answer splits almost immediately into two camps that are genuinely in tension with each other. Automated evaluation is fast, cheap, and scalable. Human evaluation is slow, expensive, and irreplaceable. … Read more
The model update arrived quietly, as they always do. No email, no warning, no entry in your changelog. The API returned a 200. The outputs looked approximately right. But three days later, a support queue had doubled — the AI assistant that previously handled refund queries had softened its responses so much that customers were … Read more
Google Analytics 4 gives you a lot of data. Whether it gives you useful insights is a different question. The GA4 interface is comprehensive but not exactly intuitive, and the jump from “I can see these numbers” to “I know what to do about them” requires either significant experience with the tool or enough time … Read more
Getting useful charts out of spreadsheet data has always been more friction than it should be. Polymer and Bricks both try to fix this with AI, but they take very different approaches — one replaces the spreadsheet as a visualisation tool, the other enhances it from within. Which one makes sense depends almost entirely on … Read more