The difference our work makes is in how the business performs.

These engagements show how we help organizations choose where to invest, put risk controls into practice, support new ways of working, and build systems that improve daily operations.

We omit client names and identifying details to protect confidentiality.

AI investment focused on priorities that justified the commitment.

Quick-service restaurant franchise groupAI Strategy & Executive Advisory

The business challenge

The franchise group wanted to improve restaurant profitability by reducing food waste and making better staffing decisions. Sixteen AI proposals competed for funding, but corporate and franchisee leaders disagreed on which would deliver enough value to justify the cost.

What we delivered

We assessed the proposals, tested vendor claims against store-level data, and agreed funding priorities with corporate and franchisee leaders. The plan put food-waste forecasting first and identified the timekeeping-data improvements needed before scheduling could proceed. Each funded priority had a named owner, a measurable baseline, and a 90-day review.

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16 → 2

AI proposals assessed to priorities funded

Why it matters

Leaders directed funding toward reducing food waste and improving staffing, and avoided tying up capital in a voice-ordering rollout with a projected payback beyond six years.

Quality teams closed records faster while leaders gained greater control over AI use.

Pharmaceutical manufacturerAI Governance & Risk

The business challenge

Quality teams needed to clear a backlog of deviation records while protecting the integrity of regulated documentation. An uncontrolled AI-generated draft triggered a company-wide ban, but employees continued using consumer AI tools outside the approved process.

What we delivered

We established separate approval paths for quality-related and general-business uses, evaluated vendors, and qualified a platform with audit-trail and data-retention controls. We defined human authorship and review requirements for AI-assisted documentation, while client quality and regulatory leaders retained decision authority.

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12 → 7

business days: typical closure time

From investigation completion to deviation-record closure.

Why it matters

The manufacturer reduced documentation delays and unapproved AI use while keeping quality decisions with qualified people. Leaders gained a record of AI approvals, controls, and accountability that stood ready for a licensing partner’s quality audit.

Customer-service teams made AI part of their work and kept using it after we left.

Wholesale building-supplies distributorAI Adoption & Transformation

The business challenge

The distributor needed more consistent quote follow-up and fewer order-detail corrections. Its investment in an AI assistant had gained little traction with frontline teams, and an inaccurate response had damaged trust in the tool.

What we delivered

We worked alongside frontline teams to develop AI-assisted workflows around their customer-service tasks, including drafting replies from order history. Representatives reviewed and edited drafts before sending them, and leaders demonstrated the practices in operations reviews. Teams helped decide which workflows continued, and we stopped a handoff-notes pilot they rejected.

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63%

weekly use two months after the engagement

Why it matters

The investment began supporting everyday customer work, and teams continued using it after the engagement ended. Quote follow-up improved and correction callbacks declined alongside changes to team workflows, giving the business evidence of value beyond license purchases and training attendance.

The firm handled more peak-season work without adding permanent staff.

Regional accounting and advisory firmCustom AI Engineering

The business challenge

Manual document preparation limited how much client work the firm could take on during its busiest season. Senior accountants spent close to a third of their time preparing files, while the firm relied on temporary hires to manage demand.

What we delivered

We built a document-preparation system that classified incoming files, extracted key information, and checked submissions against engagement requirements. It connected to the firm’s existing practice-management system, flagged missing information, and routed uncertain results to staff for review.

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+23%

peak-season engagements with the same permanent headcount

Preparation time fell from 5.5 hours to about 45 minutes per engagement.

Why it matters

Senior accountants regained time for client work, and the firm handled more engagements with the same permanent team. Temporary-staff savings alone covered the build cost in the first busy season.

What would better performance look like in your business?

Bring us the decision, bottleneck, or workflow you need to improve. In just 15 minutes, we will discuss what needs to change, what stands in the way, and whether we can help.

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