Innovation & engineering
Ideas for solving hard software problems — from custom platforms and Canadian innovation to testing, engineering judgment, and quality in demanding industries.
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Operating-System Engineering: What to Decide Before You Build
A practical guide to hardware, recovery, updates and evidence for Canadian defence, public-sector and dual-use teams planning specialized software.
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Physical AI and IoT: Decide What Runs at the Edge
Define device, site and remote-service boundaries before a physical AI pilot: connectivity, data flows, operator control and evidence for deployment.
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When Does Your Innovation Need a Custom Platform?
Five questions for Canadian innovators deciding between existing tools and a custom platform, from operational constraints to evidence and data residency.
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Conversational AI: From Dialogue to Useful Work
Our perspective on conversational AI innovation: connecting intent, context, and evidence, with a look at what TestLauncher is exploring.
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What Is Software Testing For? A View Through JTBD, Rapid Software Testing, and Deming
Software testing should reveal threats to customer progress, inform decisions, and help teams improve the system that produces quality.
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From CSV to CSA: the validation playbook the FDA just rewrote
From CSV to Computer Software Assurance: how FDA, GAMP 5, EU Annex 11 and the AI Act are converging — and how to make validation an owned asset instead of a binder.
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$2.41 trillion: the real cost of poor software quality, SaaS to smart factory
Explore CISQ’s 2022 estimate of $2.41 trillion in US software-quality costs and what it means for engineering teams and demanding industries.
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