What the work looks like when it lands.

The constraint

A manufacturer had four AI pilots running in different plants, none of which had reached production. Each had been built on a different stack by a different vendor, and none had a defined path from model output to an operator decision.

The approach

• Mapped all four pilots against a single target architecture to find what could be consolidated.
• Rebuilt the strongest use case — maintenance prioritization — as a reference implementation on shared infrastructure.
• Retired two pilots outright, with the reasoning documented for the board rather than quietly shelved.
• Left a costed roadmap where each subsequent use case reused the retrieval, evaluation, and monitoring layer.

The constraint

A mid-size lender was routing every application through a manual document review that took days and scaled only by hiring. Prior automation attempts had failed because the edge cases were where the real risk lived.

The approach

• Decomposed the review into deterministic checks, model-assisted extraction, and genuinely judgment-bound decisions.
• Automated the first two, and routed the third to a reviewer with the model's reasoning and source documents attached.
• Built an evaluation harness against historical cases before any traffic moved to the new path.
• Instrumented escalation rates and reviewer override rates as the primary health metrics.

The constraint

A utility had a load forecast that was statistically respectable and operationally ignored. Field planning ran on experience because the model gave a single number with no sense of when it was likely to be wrong.

The approach

• Rebuilt the forecast to publish calibrated intervals rather than a point estimate.
• Segmented accuracy reporting so planners could see exactly which conditions degraded it.
• Layered a scheduling optimizer that consumed the uncertainty rather than flattening it.
• Delivered recommendations with their reasoning attached, so a planner could override knowingly.

The constraint

A distributor's operations, finance, and commercial teams each reported different figures for on-time delivery. Every planning meeting began with a reconciliation argument, and no forecast was trusted enough to act on.

The approach

• Built an integration layer across the operational systems, carrier feeds, and legacy warehouse records.
• Defined a shared ontology and metric layer, so on-time delivery had exactly one definition with visible lineage.
• Layered demand and capacity forecasting on the governed foundation, with calibrated uncertainty shown to planners.
• Delivered decision surfaces that put the recommendation, its reasoning, and the source records side by side.

The constraint

A healthcare technology company had a strong underlying platform reaching users through an interface its own team described as the reason deals stalled in evaluation — and no operational capacity to maintain it once shipped.

The approach

• Rebuilt the operations console around the three workflows that accounted for most daily use.
• Deployed on managed cloud infrastructure with cost scaling to actual usage rather than peak provisioning.
• Stayed on for platform operations — monitoring, incident response, and dependency maintenance.
• Paired with their engineers throughout, so the handover date was a choice rather than a cliff.

The constraint

A manufacturing group had spent two years buying AI pilots from vendors and could not evaluate any of them. Every proposal looked plausible, every result was reported by the party being paid, and nobody internally could tell a strong architecture from a weak one.

The approach

• Ran leadership sessions on reading an AI proposal critically — the questions that separate substance from pitch.
• Taught engineering and analyst tracks using the group's own data and workflows rather than generic exercises.
• Paired with their engineers on the floor to build the first two use cases together.
• Designed the operating model — team topology, review gates, and hiring profiles for the next four roles.

The constraint

A specialist consultancy had deep technical credibility and a website that read like a template. Prospects were arriving from referral, forming a weaker impression, and arriving at the first call already discounting the firm.

The approach

• Built a design system — type scale, palette, component library — specific to the firm rather than purchased.
• Used motion and interaction to explain the delivery model instead of decorating the page.
• Produced explainer video and visual assets that survived a technical audience's scrutiny.
• Wired analytics and attribution at the source so acquisition reporting reflected actual pipeline.