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Last updated: October 12, 2026
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Organizations increasingly need to trace where training and inference data came from, how it was transformed, and whether it is compliant to use. Provenance is becoming important for governance, auditability, and model risk management.
This should grow in importance as regulation, enterprise governance, and model accountability mature. It may become a standard expectation in regulated industries and any company shipping high-stakes AI.
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<p><strong>Who we are</strong></p> <p>Artefact is a global data and AI consulting firm. We help organisations turn data and AI into measurable business impact across the value chain, from strategy and operating model to data platforms, AI products...
<p><strong>Who we are</strong></p> <p>Artefact is a global data and AI consulting firm. We help organisations turn data and AI into measurable business impact across the value chain, from strategy and operating model to data platforms, AI products...
<div class="content-intro"><h2>Our mission</h2> <p>We're making Africa the first cashless continent.</p> <p>In 2017, over half the population in Sub-Saharan Africa had no bank account. That's for good reason—the fees are too high, the closest branch can be miles away, and nobody...
<h1><strong>About Helius</strong></h1><p style="min-height:1.5em">Helius is a leading developer platform on the Solana blockchain, dedicated to inspiring and accelerating the creation of crypto-powered software. Customers like Coinbase, Jupiter, and Phantom use Helius to power...
<p style="min-height:1.5em"><strong>Chez Seyna, notre mission est simple: permettre aux professionnels de l'assurance de protéger ceux qui voient grand.</strong></p><p style="min-height:1.5em"><strong>Rejoins notre mission ! 🚀</strong></p><p style="min-height:1.5em"><a...
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