From AI adoption to accountable, validated operations.
Smart Control is an independent AI Risk & Accountability initiative developed through Mataya Ltd, helping organisations turn AI adoption into operations they can own, validate and be held accountable for. Built on one conviction: AI that can't be owned or validated isn't ready to depend on.
A founder who's watched the gap widen, and chose to close it.
Laurent created Smart Control after years watching organisations race to adopt AI, then struggle to answer the questions that make it safe to depend on. Who owns each use case? What was it validated against? Where is the evidence? Who is accountable when it goes wrong? Too often the answers arrived after the problem, not before it.
Based in Aotearoa New Zealand and supporting organisations across New Zealand, Australia and internationally, Laurent brings a cross-market perspective: the pragmatism of the Antipodes and the regulatory rigour of Europe. The result is independent advice and practical implementation, rigorous enough to defend, pragmatic enough to actually ship.
Smart Control stays deliberately independent and vendor-neutral. No product to sell, no model to favour, only independent advice on how to make your AI adoption accountable, validated, and defensible.
“My earlier career in aerospace exposed me to environments where risk, validation, evidence and accountability could never be treated as optional. Later, working as a Business Analyst and Salesforce Consultant, I watched organisations adopt increasingly powerful digital systems while facing similar questions around ownership, control and decision-making. Smart Control emerged from the observation that AI adoption was advancing faster than the structures needed to keep it accountable. Today, I help organisations establish practical approaches to AI Risk & Accountability that support adoption without losing control.”
— Laurent Torlois
Meaningful, not performative
If the validation can't change a decision, it isn't validation. We build ownership, evidence and accountability into AI use before and during deployment, not as paperwork after the fact.
Independent by design
No vendor relationships, no models to favour. The only thing we defend is your evidence, independent advice given without conflict.
Practical rigour
Risk and validation your teams can operate and your regulators will accept, accountability that works in practice, not policy that satisfies neither.
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Laurent works directly with every engagement.