Case Studies

Real work,
documented honestly.

Detailed case studies are in development. We're being deliberate about what we publish — anonymizing where required, getting client approval, and writing in enough depth that they're genuinely useful, not promotional.

— What we publish

Most consulting firms' case studies read like sales brochures. We're aiming for something different — case studies that are useful to practitioners, not just impressive to procurement.

Each one will cover: the actual technical problem, the architecture decisions we made and why, what we'd do differently in hindsight, and measurable outcomes. Wherever possible, with client permission, named. Where confidentiality requires it, thoroughly anonymized.

We'd rather publish three detailed, useful studies per year than twelve generic ones. The first will go live as soon as we have approval to share it properly.

In Progress

What's being prepared.

A preview of the case studies in development. Subjects, not specifics — names and details will appear when published.

In Preparation
Professional Services · Multi-Office

Unifying performance reporting across a multi-office firm

How a regional professional services firm replaced fragmented office-level reporting with a unified analytics platform. Covers integration across billing, time tracking, and finance systems, the metrics that mattered most to firm leadership, and how partners now spot performance trends weeks earlier than before.

In Preparation
Electrical Engineering · Industrial Services

Bringing project and asset data together for an electrical contractor

How a regional electrical engineering and contracting firm replaced fragmented project tracking with a unified analytics platform. Covers integration across job costing, fleet, and field operations systems, the metrics that mattered most for project margin and crew utilization, and how leadership now spots performance drift before it eats profitability.

In Preparation
AI Integration

When NOT to use AI

An honest study of a project where we recommended against the AI solution the client originally wanted — and built a simpler, cheaper, more maintainable alternative instead. The case for restraint in AI consulting.

Why this matters

Most case studies are useless.

They're written for marketing, not learning. Generic wins, vague metrics, vendor logos. They tell you nothing about how the work actually got done.

We're trying to write case studies the way good engineering teams write post-mortems — with specificity about what we built, why we built it that way, what worked, what didn't, and what we learned. Useful to read whether or not you ever hire us.

That takes time and care. But it's the only kind of content worth publishing.

Have a problem worth documenting?

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