The product thinking of big tech.
The speed of a boutique.
AI strategy consulting and product advisory for mid-market companies — from first mandate to full deployment.
For mid-market companies navigating AI transformation — a senior product partner who qualifies the problem before committing to a solution, then stays through implementation.
Most consultants assume you have an implementation team waiting. You do not. That is exactly the problem this model solves.
Most AI projects fail before they start.
A clinic invested heavily in AI tooling for its consultants — patient intake, workflow automation. The project was delivered on time. The technology worked.
The consultants did not adopt it. The ROI never materialised.
Nobody had asked what trust looked like for the people using it. Nobody had defined what success looked like before the build began. Nobody had run a small sponsored pilot before committing the full budget.
The technology was not the problem. The problem was that nobody qualified the problem first.
This is the pattern. We have seen it across health tech, ecommerce, SaaS, and enterprise software. And it is always preventable — if the right questions are asked in the first two weeks.
A product management standpoint.
Not a consultancy process.
A consultant runs a framework. A product executive runs discovery — on the organisation itself.
Before recommending anything, we map long-term company objectives against short-term team incentives. We surface misalignments nobody has said out loud. We ask what trust looks like for the people who will use the system. We define success metrics jointly, before anyone writes a line of code.
Then — and only then — we decide what to build.
That instinct was trained across a decade at Google, in health tech, Android developer platforms, and connected devices. Environments where the cost of building the wrong thing is measured in real harm, not just wasted budget. That discipline now works at your scale.
One journey. Three stages. Every engagement starts at the beginning.
The Diagnostic
Two to three weeks · Fixed feeWe qualify your problem before anyone commits to a solution. You leave with an agreed AI strategy, a prioritised roadmap, and a scoped brief — ready for leadership and ready to build from.
How the Diagnostic works→The Sprint
Four to eight weeks · Fixed fee agreed after the DiagnosticA focused build on the highest-priority opportunity. Working prototype on your real data. Evaluation results. A clear recommendation on whether and how to invest in full production.
How the Sprint works→The Partnership
One day per week · Minimum three monthsA senior product partner embedded in your organisation. Roadmap sequencing, team upskilling, talent access, and ongoing AI bet prioritisation. The goal is a team that operates independently. We make ourselves unnecessary.
How the Partnership works→Two situations come up most.
The board mandate.
A senior director or VP is asked by their executive team to come back with an AI strategy and a plan for investment. They need someone who has been in that room before — who can talk to practitioners and board in the same week, spot where the organisation is pulling in different directions, and surface the pivots nobody inside has permission to name.
The product under threat.
A SaaS company or consumer product business is watching LLMs absorb what made their product valuable. They need someone who can look beyond the constraints of what has been, toward what might be — and help them find the competitive moat that is still available to them.
Both situations start with the Diagnostic.
Named for three reasons.
lerad-ai is named for Leo, Raphaël, and Danyël. Three children. Three reasons to do work worth doing.
Fabien Cardineau spent a decade shipping AI at Google — health tech used by millions, Android developer platforms, connected sensor infrastructure. He left to bring that same rigour to companies that do not have a Google-sized team behind them, and to build a business designed around his life.
When you work with lerad-ai, you work with Fabien. Directly. Always.
What people ask before getting in touch.
What is a senior AI product partner?
A senior AI product partner combines the strategic instincts of a product executive with deep AI expertise — and embeds them in your organisation rather than advising from the outside. Unlike a traditional AI consultant who runs a framework and hands over a report, a product partner runs discovery on your organisation, surfaces the problems nobody has said out loud, defines what success looks like before anything is built, and stays through implementation. The result is AI that actually gets used.
Why do most AI transformation projects fail?
The technology is rarely the problem. Most AI projects fail because nobody qualified the problem first. Organisations commit budget before defining success metrics. They build for what is technically possible rather than what is actually executable given their data, their team, and their risk tolerance. They skip the question of what trust looks like for the people using the system. These failures are preventable — but only if the right questions are asked in the first two weeks.
What kinds of companies does Lerad AI work with?
Mid-market companies — typically 200 to 2,000 people — in two situations. The first: a senior director or VP has a board or executive mandate to develop an AI strategy and investment plan. The second: a SaaS company or product business is watching LLMs absorb what made their product valuable and needs to find the competitive moat that is still available to them. Both situations start with the Diagnostic.
How is Lerad AI different from a traditional AI consultancy?
Three differences. First, the lens: we apply product management thinking to AI transformation — which means running discovery on your organisation before recommending anything, not fitting your situation into a pre-existing framework. Second, the model: one senior partner, always. You work with Fabien directly, not a junior team. Third, the scope: we work with four clients at a time and stay through implementation. The goal is a team that operates independently. We make ourselves unnecessary.
Four clients at a time. Is there room for you?
Every engagement gets full attention from day one. We are deliberate about that.
Tell us about your situation →