AI that ships. Adoption that sticks.
Most mid-market companies have already paid for AI tooling. What they haven’t built is the path from pilot to production — or the operating model that makes adoption stick. Innovy closes both gaps. Two senior operators. Four productized engagements. One free briefing to start.
If this is your organization, we should talk.
The CEOs, COOs, and CIOs we work with — at Canadian and US mid-market companies — tend to arrive with the same five problems. They’ve bought the tooling. The work of making it produce results is still ahead of them.
Your teams have Copilot or Claude licences. Very few people are using them in any meaningful way.
Leadership can’t identify which AI investments are worth making — or build a number the CFO can defend.
Pilots keep running. Production keeps not happening. The same use cases have been in “discovery” for six months.
Nobody inside the organization owns AI. Everyone assumes someone else does.
The people who were supposed to adopt the AI that did ship are quietly ignoring it — or actively resisting it.
“We don’t need another deck on what AI could do. We need someone to tell us what to ship in the next ninety days, and then help us ship it.”
— Said to us, in some form, by every operator we’ve talked to in the last six months.
The problem we solve
Two gaps, not one.
Most mid-sized companies have already bought into AI. Copilot seats. A Claude or ChatGPT enterprise contract. Pilots in IT, finance, customer support, and operations. A slide on AI in every board pack. What they haven’t built is the path from there to AI in production.
The execution gap.
Pilots that worked in a sandbox have not become agents that run every day. There is no working number leadership can defend, no operating cadence that decides which bets to back, no clear answer to the question the team keeps asking: what should we actually be building?
The adoption gap.
The AI that does ship gets quietly ignored — or actively resisted — because the people who were supposed to use it fear it, distrust it, or were never asked. Pilots fail not because the model was wrong but because the room was wrong.
The first gap is technical. The second is human. Most firms in this market can address one. Innovy is built to close both.
What we deliver
Four products. One sequence.
Four productized engagements, designed to sequence. A client can enter at any of them; most move through the full arc — from a one-page brief to a working AI factory the organisation runs without us in the room.
(They are sequenced because, in practice, that is the order they get done in. We have tried it out of order. It does not work.)
The Executive Briefing
A couple of structured sessions with the CEO, CFO, COO, or CIO and their direct team. We share what we’ve seen in mid-market AI adoption, where the common failure modes are, and what an honest first move looks like for an organisation at their stage. We close with a written brief — a one-page read on where your organisation sits, and where the first investment should land.
AI Foundations
The operating chassis the organisation runs AI on from here forward. A governance model. An AI policy. A steering committee with named members. A budget posture — capex vs opex, project vs portfolio. An honest assessment of what has already been tried and what worked. A strategy sized for your company. A rollout plan with phasing. A tech-stack call — Microsoft, Anthropic, or both, and what to keep vs change.
AI Champions & Discovery
The use-case generation engine. Before we put a workshop on a calendar, we identify champions inside each department — the people whose colleagues already ask them how to use Copilot or Claude. We equip them with a curated training pathway, sequenced for their role, so they walk into the workshop ready to contribute. Then we run workshops alongside them, department by department, surfacing the work that AI could actually help with. The outcome is a qualified list of use cases, ranked by ROI and feasibility, with named owners.
The Execution Partnership
A retainer that helps the organisation actually ship the use cases — the productive phase of the engagement. Champions execute the simpler use cases with Innovy coaching and tooling support. Innovy delivers the complex ones — agents, integrations, governance scaffolding, vendor decisions — and runs the cadence that keeps the portfolio moving. Most consulting engagements end where the work begins. This one starts there.
Track record
Built in environments where reliability matters.
The two founders have shipped AI where failure has real consequences. That operating discipline is what we bring to your organization — not theory, not slides, not a framework that worked somewhere else.
AI in classified defence environments
Locally hosted LLM deployments using Qwen and Ollama in air-gapped, high-security environments where commercial cloud is not available. AI governance and policy built from the ground up for settings where the stakes of getting it wrong are not recoverable.
Digital twin implementation
Design and deployment of a digital twin solution for a medium-to-large defence organization, integrating real-time operational data into a live simulation and decision-support environment.
Autonomous agents, shipped
Production deployments including a Chief of Staff AI agent that gathers multi-system data, drafts executive summaries, and prepares briefings — and an end-to-end content pipeline that produces and distributes content across LinkedIn, Facebook, and Instagram autonomously.
Naval modernization & infrastructure programmes
Twenty-five years delivering programmes with Lockheed Martin and Thales on Royal Canadian Navy modernization — HMCS Vancouver and HMCS Regina — and nine years leading engineering operations at the Department of National Defence. Over $130M in programmes managed.
Example outcomes
What we’ve shipped.
Client names are withheld. The work is real.
Chief of Staff Agent
Challenge
Executives spent several hours each week consolidating updates from multiple internal systems and preparing briefings for leadership meetings.
What we built
An autonomous AI agent that gathers information from across the organization, drafts consolidated summaries, and prepares executive briefings on a schedule.
Result
Preparation time reduced from several hours to minutes. The work that remained was judgment, not assembly.
Canadian professional services firm — name withheld at client request
Content Distribution Pipeline
Challenge
Publishing consistent content across LinkedIn, Facebook, and Instagram required manual effort across multiple platforms, creating bottlenecks and inconsistency.
What we built
An end-to-end AI workflow that produces content, formats it for each platform, schedules publication, and distributes autonomously across all channels.
Result
Content distribution became a largely hands-off process. The team’s time shifted from execution to strategy.
Canadian SME — name withheld at client request
What you walk away with
The brief. One page. Four questions.
Most consulting engagements end with sixty slides. Ours starts with one page — a written brief, in operator’s prose, sized for the room and short enough to re-read on a Sunday. Every engagement is different. Every brief answers the same four questions.
Where are you actually?
A clean read on what’s deployed, what’s adopted, what’s drifting, and what no one has measured yet.
What is the first move worth making?
The single highest-leverage bet — scoped to a function, a window, and a cost.
How will you know it worked?
A measurement scaffolding finance can read inside a quarter, not a year.
What should you stop doing?
The pilots, vendors, and meetings worth retiring. Saying no on purpose.
No frameworks. No abstractions. A working answer you can act on Monday.
How we’re different
Four wedges.
Most firms in this market lead with a tool and try to fit your organisation around it. We lead with the people who will use what we ship — and the platform decisions flow from that.
We start with the people, not the platform.
Most firms in this market lead with a tool — Copilot, Claude, an agent platform — and try to fit the organisation around it. We start with the question of who will use what we ship, and whether they will trust it. The platform decisions flow from that.
We build capability inside your team.
The AI Champions methodology is the operating expression of that belief. By the end of Discovery, you have people inside your organisation who can carry the work forward. By the end of the Execution Partnership, the factory runs without us in the room. Dependency on us is not our business model.
Tool-agnostic, on purpose.
We work across Copilot, Claude, and the agent platforms behind them. Sometimes the right answer is Microsoft. Sometimes Anthropic. Often both. We do not resell licences and we will recommend against a tool when the work calls for it.
Factory discipline, mid-market sized.
We bring an enterprise AI-factory playbook — the small group that decides what to ship, the engineer who ships it, the finance partner who measures what it returned — and size it for an organisation that does not need a fifty-person Center of Excellence.
A note on fit
What Innovy is not.
Saying what we are not is part of saying what we are. The clarity protects the work — and saves everyone’s time.
We don’t place AI engineers in your seats. The team that ships with us is ours. The capability we leave behind is yours.
We work with Microsoft tools because they’re dominant in our segment. We’ll recommend against them when the work calls for it. We don’t earn a referral fee either way.
Change practices are embedded in how we deliver. But the deliverable is shipped use cases and a working operating model — not a training programme.
Most engagements in this market end with a deck nobody reads. Ours starts with one page you can act on Monday — and ends with working software in production.
Founders
Two operators.
Innovy is run by two operators who have built and shipped AI inside the organisations we now serve. Material decisions — pricing, hires, product additions, market expansion — are made together.
Wassim Mawas
Chief Executive · Program & Delivery
I have shipped AI inside an enterprise. Most of what gets sold as AI strategy would not survive contact with the room I have been sitting in.
Enterprise transformation leader with experience spanning General Electric, large-scale infrastructure and technology programs, operational excellence, digital transformation, and enterprise AI adoption. Built and operates enterprise AI Factory capabilities that combine governance, enablement, use-case discovery, and execution. Known for aligning executives, engaging frontline teams, and turning emerging technologies into measurable business outcomes.
Executive AI Strategy — Facilitated executive AI strategy sessions translating into AI and business priorities alignment, investment decisions, and measurable outcomes.
AI Champions Program — Established AI Champion networks that accelerated grassroots adoption, capability development, and use-case identification across organizations.
Stephen McCormick, P.L.Eng.
Chief Technology Officer · Canada GTM
Strategy is the easy part. The hard part is shipping it — and making it run after we leave the room.
Senior operations leader with more than twenty-five years helping complex organizations execute large-scale initiatives in high-reliability environments. Defence career spanning Lockheed Martin, Thales, and the Department of National Defence — leading cross-functional teams and translating strategy into measurable operational outcomes. Focused now on helping organizations move from AI strategy to hands-on adoption, with a particular strength in coaching experienced teams through the change.
Operational AI Adoption — Helps organizations move from AI strategy to working AI in operations — building the structured implementation roadmaps that make adoption stick, especially in teams that have already tried and stalled.
Engineering Leadership & Coaching — Twenty-five years leading and mentoring cross-functional engineering teams in high-reliability environments. Brings that same coaching discipline to helping experienced professionals build confidence with new technology.
What we believe
Our point of view.
AI succeeds or fails on adoption, not on technology. The hard part of this decade will not be the models — it will be the change management around them.
The companies that win will be the ones whose employees can use AI, want to use AI, and trust the way it was deployed. The technology layer is solvable. The human layer is harder, and most of the market under-invests in it.
Productivity comes first. We help the people already doing the work do more of it, better, faster — with AI in their hands. If reorganisation follows later, we will help with that too. But reorganisation is never the objective.
AI is closer to manufacturing than to research. The companies that win will run it that way — a small group that decides what to ship, an engineer who can ship it, a finance partner who measures what it returned, and the people doing the work helping decide what to build next.
Mid-market companies, not the Fortune 500, will produce the cleanest case studies of this decade — because they are small enough to move and big enough to measure.
Common questions
What executives ask us.
Answers to the questions that usually come up before anyone sends an email.
An invitation
If you have read this far, let us write you a brief.
Two sessions with you and your team. We come in, ask the questions we already know are the right ones, and listen for the ones we don’t. A week later, you have a one-page written brief on where your organisation actually is with AI, and where the first move should land.
No deck. No fee. No follow-up sequence. We do it free because, in our experience, the brief is how we earn the right to the rest of the work — and if it is not for you, you keep the brief and we part ways well.