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On discovery, back offices, and where AI actually helps.

We don’t publish often — only when there’s something concrete to say. What’s here tends to cluster around a few threads: finding out what to build before anyone writes code, putting AI inside real workflows (inboxes, order desks, quotes), connecting the systems you already pay for, and the build-or-buy calls operators face every month. Written for people who run the work, not for developers chasing trends.

Showing 1–6 of 8 in strategy

Two laptop screens side by side: one showing a generic SaaS dashboard, the other a bespoke web app — the build-vs-buy decision in physical form.

Build vs buy: the question we get asked the most

After 20 years of these conversations, here's the honest framework we use to help businesses decide whether to build something bespoke or live with off-the-shelf software.

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A customer-services agent at her desk reviewing an AI-drafted reply on screen, finger hovering over the send button.

AI in customer services: a draft on every reply

How AI changes the shape of a customer-services inbox — reading inbound messages, looking up the customer and order across your systems, and putting a draft reply in front of a person who still presses send.

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A scanned purchase order on the left of a monitor, beside a clean structured-data view of the same document — line items extracted, products matched against the catalogue, exceptions flagged.

AI for document understanding: POs in, structured data out

Purchase orders, supplier price lists, delivery notes — the documents your back office still re-types by hand. How AI plus a few well-chosen MCP lookups turns the order desk from a typing job into a judgement job, with humans on the exceptions.

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A salesperson reviewing an AI-drafted quote on screen — line items, prices, stock indicators and lead times all assembled from internal systems, ready for her to set the margin and send.

AI for the back office: drafting quotes from your own data

The outbound mirror to the two inbound AI posts. How AI assembles a draft quote from your own data — customer history, contracted pricing, stock, lead times — and lands it on the salesperson's desk. They set the margin and press send. With a look at where this naturally leads next: customer and quote portals.

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A small business owner and a developer at a desk, looking at a screen showing a clean integration diagram between named systems like Xero, a courier and a CRM.

A business owner's guide to APIs

What an API actually is, in plain English — and the three places they quietly change a business: how customers talk to you, how you talk to your suppliers, and how your own systems start talking to each other.

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A B2B customer logged into a clean portal on her laptop, looking at her account's open orders, recent invoices and a draft quote awaiting her approval — coffee mug beside her.

Customer & quote portals: where customers do the work themselves

The natural follow-on to the AI-drafted quotes post. What a portal actually is, where AI sits inside it, and the awkward bits nobody mentions until you're three months in — pricing visibility, the self-service/human boundary, and how to roll one out without upsetting customers who love email.

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