Case studies · engagement patterns

From ambiguity to measurable transformation.

Three deep dives into how leadership teams move from scattered AI experiments and legacy constraints to focused strategy, working systems, and organizational change.

Let’s talk → All six engagement patterns

These describe representative engagement patterns and the approach taken — the shape of the work, not specific client results.

Engagements

Three deep dives.

Each engagement is unique, but the pattern repeats: diagnose the system, prioritize ruthlessly, build something real, and design for adoption.

ProductExec Operating Model Governance

Series B SaaS — Product Operating Model Reset

Challenge

A scaling B2B SaaS company had outgrown its startup-era product process. Four stakeholders owned overlapping pieces of the roadmap. Discovery was ad-hoc. Releases shipped without clear success criteria.

Approach

Redesigned the product operating model: established single-threaded ownership, introduced a discovery cadence with defined validation gates, reset the roadmap governance rhythm, and aligned metrics to business outcomes rather than output.

What good looks like

A roadmap the executive team reviews as a set of strategic bets rather than a feature backlog — single-threaded ownership, a repeatable discovery cadence, and a shorter path from decision to delivery.

Enterprise AI Studio AI Strategy Healthcare

Healthcare Platform — AI Strategy Alignment

Challenge

A healthcare technology company had 12 AI ideas across product, ops, and clinical teams — but no framework for choosing which ones deserved investment. Trust and compliance constraints made experimentation risky.

Approach

Ran a structured AI opportunity assessment: mapped each idea against customer value, technical feasibility, regulatory risk, and organizational readiness. Built a prioritized implementation sequence with clear decision gates.

What good looks like

Leadership aligned on a small number of high-confidence bets instead of a long list, with the first pilot scoped against explicit success criteria and compliance guardrails before any scale decision.

Enterprise AI Studio Automation Pilot

Automotive Retail — Workflow Automation Pilot

Challenge

Fragmented manual workflows across customer intake, follow-up scheduling, and performance reporting. A large share of staff time went to repetitive coordination that could be automated.

Approach

Mapped the end-to-end workflow, identified automation-ready segments, built a working pilot for the highest-value process (customer intake + automated follow-up sequencing), and designed the adoption plan for frontline staff.

What good looks like

A bounded pilot on one high-volume workflow, measured against a documented baseline, with an expansion path defined only for workflows that clear the pilot’s success criteria.

Methodology

How the work moves.

A repeatable approach to turning ambiguity into systems that outlast the engagement.

Diagnose

Understand the system before prescribing. Map workflows, decisions, constraints, and stakeholder dynamics.

Prioritize

Not every opportunity deserves investment. Filter by value, feasibility, risk, and organizational readiness.

Build

Start with a scoped pilot that proves the thesis. Working systems beat strategy decks.

Scale

Design for adoption from day one. Metrics, ownership, and governance that outlast the engagement.

Next step

Ready to move from ambiguity to action?

Tell me about the constraint, the opportunity, or the question your team is stuck on. I’ll let you know if I can help.

“I have rarely met a Product leader more aware of the value of customer experience and customer support as Kevin is.”
Simone Secci · CX & Support Ops Consultant

Let’s talk → See all engagement patterns