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Perspectives from our engineers and consultants on scaling AI beyond the pilot, governing data, modernizing critical systems, and building the capabilities that power innovation—written for the leaders who make the decisions.
· AI · 2 min read
Beyond the pilot: Why most AI initiatives stall before production
The gap between a successful pilot and a system in production is rarely about the model. It is about evaluation, ownership, and integration.
Read more· AI · 2 min read
Build, buy, or borrow? A decision framework for large language models
When to call an API, when to host a model, and when a vendor product is the right answer—and why the decision should be revisited every six months.
Read more· Data · 2 min read
Is your data ready for AI? Five questions to answer before choosing a model
The questions we ask at the start of every AI engagement—and why the answers usually point to the data before the model.
Read more· Engineering · 2 min read
Modernizing in slices: Why incremental modernization outperforms the big bang
Large rewrites fail in predictable ways. The strangler pattern is older and less glamorous, and it is the approach that works.
Read more· AI · 2 min read
Evaluating AI systems: What benchmarks cannot tell you
Public benchmarks measure a model on someone else’s task. An evaluation framework measures the whole system on yours.
Read more· Governance · 2 min read
Responsible AI in Canada: The rules that apply today
Law 25, PIPEDA, and sector regimes already govern AI systems in Canada—whatever happens to federal AI legislation.
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