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Insights & Ideas
Research, engineering deep-dives, and product thinking from the Loretto AI Labs team.
The $8 billion Australian removalist market has operated with minimal technology innovation for decades. Fragmented marketplaces, opaque pricing, and a near-total absence of trust infrastructure have left both customers and providers underserved. We built Moverspot to change that — and in doing so, we learned a great deal about what it takes to apply AI effectively in a complex, high-stakes service market. This is what we found.
From concept to launch: how we designed, built, and iterated on 14 AI agents to power Australia's first intelligent removalist marketplace.
Off-the-shelf pricing tools couldn't handle our auction model requirements. Here's the architecture we built — and what we learned along the way.
Marketplaces are adversarial environments. We detail the four-layer fraud detection system we built for Moverspot and the principles behind it.
Our architectural journey: why we chose a microservices approach, how we manage it with Nx monorepo tooling, and the trade-offs we made.
Users don't read terms and conditions — they feel trust or they don't. How we approached trust design in Moverspot's customer and mover interfaces.
Melbourne is Australia's startup and creative capital. But it is also underserved by deep-tech AI companies. Here's why that makes it the perfect place to build Loretto AI Labs.
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