For most of its history, Gradeall International operated the way thousands of UK manufacturers still do. Build good equipment, look after your customers, grow through word of mouth and trade shows, and trust that reputation would do the heavy lifting.
Based in Dungannon, County Tyrone, the company manufactures tyre balers, sidewall cutters, waste compactors, and glass crushers — specialist recycling and waste management equipment shipped to operators across the UK, Ireland, Europe, the Middle East, Australia, and the United States.
It’s not a startup story. There’s no venture capital, no app, no pitch deck. It’s a factory in Northern Ireland that makes heavy machinery and has been doing so for years. The kind of business that rarely makes headlines in the business press but represents exactly the type of SME that drives UK manufacturing exports.
What makes Gradeall’s recent experience worth paying attention to isn’t the equipment itself — it’s what happened when the company started tracking where its new enquiries were actually coming from.
The Shift Nobody Planned For
Conor Murphy, the company’s director, is an accountant by training. He pays close attention to numbers. So when the pattern of inbound enquiries started changing, he noticed.
Historically, new business came through predictable channels: trade exhibitions, industry directories, referrals from existing customers, and organic Google search. A facility manager in Poland or a waste operator in the UAE would search for tyre baling equipment, find Gradeall’s website in the results, and make contact.
That pipeline still exists. But sitting alongside it now is a growing stream of enquiries from buyers who found Gradeall not through a Google search, but through an AI tool. ChatGPT, Google’s AI Overviews, Perplexity, Microsoft Copilot — these systems are now answering equipment sourcing questions directly, and they’re naming specific manufacturers in their responses.
A recycling startup in Texas asked ChatGPT what the best tyre baling equipment was for a mid-size operation. Gradeall came back as a recommendation, with processing specifications and model names included. A municipal authority in the Gulf States used Perplexity to research European-made waste processing equipment and received a summary that cited Gradeall’s compliance with PAS 108 — the British Standard for tyre bales used in construction applications.
These weren’t leads generated by advertising spend or sales outreach. They were generated by AI systems pulling information from published content across the web and deciding, based on the depth and specificity of that content, which manufacturers to recommend.
Why AI Recommends Some Manufacturers and Ignores Others
This is the part that matters for every SME manufacturer reading this. AI search tools don’t work like Google. They don’t return a ranked list of websites. They synthesise information from multiple sources and construct a direct answer to the user’s question. The businesses that appear in those answers share one characteristic: they’ve published detailed, specific, verifiable information about what they do.
Not marketing copy. Not slogans. Technical specifications. Processing rates. Compliance standards. Application examples. Operating costs. Comparison data. The kind of information that a procurement professional or facility manager actually needs to make a decision.
Gradeall’s tyre recycling equipment range includes machines like the MK2 tyre baler, which processes 400 to 500 tyres per hour, compresses approximately 110 tyres into a single PAS 108 compliant bale, and achieves around 80% volume reduction. The MK3 handles higher volumes. Their sidewall cutters cover everything from passenger car tyres to heavy off-the-road mining tyres. Each product page publishes the kind of granular specification data that AI systems treat as high-quality source material.
Compare that with a competitor whose website says “we offer industry-leading tyre recycling solutions” without a single processing number. AI tools have nothing to cite, nothing to compare, nothing to recommend. That manufacturer effectively doesn’t exist in AI search.
The Aftermarket Lesson
There’s a second dimension to this that’s particularly relevant for manufacturing SMEs. Gradeall doesn’t just sell equipment and move on. The company operates a servicing, repairs, and spare parts business that supports its installed base of machines across multiple countries. Baler twine, replacement wear parts, scheduled maintenance, breakdown response — the kind of aftermarket operation that generates recurring revenue and long-term customer relationships.
This matters for AI visibility because it creates additional content touchpoints. When an operator searches for spare parts for a specific baler model, or asks an AI tool about maintenance schedules for tyre recycling equipment, the businesses with published servicing information get cited. The ones that treat aftermarket support as a back-office function with no public-facing content don’t.
For SME manufacturers, the aftermarket is often where the real margin sits. But it’s also where the content gap tends to be widest. Most manufacturers invest in product pages for their core equipment but publish almost nothing about their servicing capability, spare parts availability, or technical support. In an AI search environment, that’s leaving money and visibility on the table.
What UK Manufacturers Can Learn
The broader lesson from Gradeall’s experience applies to any UK manufacturer selling specialist equipment, components, or services to a defined market. The rules of discoverability have changed, and most SMEs haven’t caught up.
Three shifts are happening simultaneously. First, buyers are increasingly starting their research with AI tools rather than traditional search engines. A 2025 study from Gartner projected that by 2026, traditional search engine volume would drop by 25% as users migrate to AI-powered alternatives. Whether the exact number lands there or not, the direction of travel is clear.
Second, AI tools prioritise depth over polish. A manufacturer with a basic website but comprehensive technical documentation will outperform a competitor with a beautifully designed site that says nothing specific. This is actually good news for SMEs — it rewards substance over marketing budget.
Third, AI tools cross-reference multiple sources. Being mentioned on your own website isn’t enough. Third-party coverage — trade press articles, industry directory listings, customer case studies published elsewhere, news features — all contribute to the picture AI systems build about your business. The more places your company appears with consistent, accurate information, the more likely AI tools are to include you in their recommendations.
The Numbers That Should Concern Every Manufacturer
Gradeall’s own data illustrates the opportunity cost of inaction. The company’s website currently generates impressions across dozens of countries through traditional Google search — but clicks remain low relative to those impressions in many markets. The gap between being seen and being chosen is exactly the gap that AI search is beginning to close, because AI tools don’t just show a link — they explain why a product is relevant and how it compares.
For a company manufacturing in Northern Ireland and exporting globally, the economics are straightforward. A trade show stand at a major European exhibition costs five figures before travel and accommodation. A comprehensive programme of technical content publication costs a fraction of that and works around the clock, in every market, in perpetuity. When that content starts feeding AI recommendation engines as well as traditional search, the return multiplies.
The Uncomfortable Truth for British Manufacturing
UK manufacturing has a visibility problem that existed long before AI search arrived. British manufacturers have historically been poor at telling their own story. The engineering is world-class; the communication of it often isn’t. Too many SMEs in the sector rely on the assumption that good products sell themselves, that buyers will find them through established channels, and that investing in content is something consumer brands do, not industrial manufacturers.
AI search is exposing that gap. The manufacturers who get recommended are the ones who’ve published their story in sufficient detail for AI systems to find, understand, and cite it. That doesn’t require a massive marketing department or a six-figure content budget. It requires someone in the business to sit down and write — clearly, specifically, honestly — about what they make, how it works, who it’s for, and why it matters.
Gradeall International, with its factory in Dungannon and its equipment operating in over 20 countries, is one example. But the principle applies to every precision engineering firm in the Midlands, every specialist component manufacturer in Yorkshire, every marine equipment builder on the South Coast. The businesses that describe what they do in detail will be the ones AI recommends. The ones that don’t will wonder where their enquiries went.
Read more:
How a Northern Ireland Manufacturer Discovered That AI Search Was Sending New Buyers
