The scenarios below reflect the kind of problems I work on and how I approach them. Each one is drawn from real challenge patterns I have encountered across consulting, government, and technology environments. The organizations are fictitious. The thinking is not.
Challenge
Ironframe was a Series B construction tech company with 1,200 customers and no AI strategy. Three teams had independently prototyped AI features. None had shipped. The board was pushing for AI-powered differentiation ahead of a Series C raise, but the executive team was pointed in three different directions and governance had not been considered.
The work started with aligning leadership around a single sequenced roadmap, establishing a governance framework before any build began, and moving the company from zero AI in production to a customer-validated proof of concept in 90 days.
Outcome Ironframe entered its Series C raise with a credible AI story.
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Meridian was an 800-person consulting firm running on spreadsheets. Over 120 reports in circulation. Fewer than 30 actively used. Analysts spending 60% of their time formatting data rather than analysing it. A $4M discrepancy in the corporate rollup that nobody had formally resolved.
The work started not with building, but with retiring. Sixty-two reports were decommissioned in the first 30 days. Metric definitions were agreed before any dashboard was built.
Outcome By month seven the CFO closed the books using a live platform for the first time, with no manual reconciliation step.
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Halcyon had deployed three machine learning models to support caseworker decisions across social assistance, employment, and housing programs. An internal audit found the models could not be adequately explained. A formal complaint had been filed with the provincial privacy commissioner. The Deputy Minister needed a defensible plan for the minister's office within 60 days.
The work involved reframing the problem from a technology failure to a governance failure, stabilizing the situation through mandatory human review requirements, remediating the models with explainability layers, and building a responsible AI framework that the agency adopted as policy.
Outcome The privacy commissioner closed the complaint file in month twelve and noted the agency's approach as an example of responsible institutional response.
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Vantage Loop had shipped seven AI-powered features across their HR platform in two years. No central inventory. No bias testing. No documentation that would satisfy an enterprise procurement team. A financial services deal stalled on 31 unanswered due diligence questions. A public sector opportunity lost to a competitor with better documentation.
The work involved auditing all seven features, building a responsible AI framework co-owned by the product organization, completing model cards and bias testing across every consequential feature, and turning AI governance into something the sales team could use to win deals.
Outcome The financial services deal closed in month four. Bias testing found a real performance gap; the feature was pulled, fixed, and relaunched. One enterprise client expanded their contract three months later.
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Crestwood was a privately held holding company with three business units, $320M in annual revenue, and no shared data infrastructure. Monthly reporting was assembled manually by finance leads. The same metric was calculated four different ways across four teams. The board was pushing for portfolio-level decision-making that the executive team did not have the tools or the fluency to support.
The work started with a decision inventory: ten decisions the executive team actually needed to make, and what information would make each of them better. Everything built from that point was anchored to those ten decisions. A structured executive data fluency program ran alongside the platform build.
Outcome By month eight, the CEO walked the board through three months of portfolio performance data without notes, without a slide deck prepared by the finance team, and without deferring to the CFO for interpretation.
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