About the studio

A studio for the work AI keeps making harder, not easier.

LeapFactors is an applied AI studio for founder-led mid-market companies. We design, build, and embed the systems that actually move the business — and we bring the people along for the ride.

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What the studio is

What the studio is, and why it exists.

LeapFactors is a US-based, solo-founded applied AI studio. The work is small on headcount and wide on craft — Aaron Rutherford with a tight orbit of contractors and partners, working inside founder-led mid-market companies that have outgrown DIY AI but can't reasonably hire a Big Four firm or a 200-person AI integrator.

The studio exists because of a gap that most of the AI industry has stopped pretending isn't there. Below the enterprise tier and above the prosumer tier — somewhere between $10M and $250M in revenue — sits the bulk of American operating businesses. They are profitable. They are run by people who built them. They are watching the AI conversation closely. And almost none of the existing options serve them well.

Big consultancies sell them slide decks they can't afford. AI dev shops will write code but won't speak the business. Vertical SaaS platforms ship features that close maybe sixty percent of the gap. None of these options put the same person in the boardroom and on the build, and almost none of them take seriously what AI does to the people who actually do the work.

LeapFactors is a different thing. A studio. A place where the work gets made. We are operators, not slide-makers, and we are explicitly on the workforce's side.

What we believe

Four things we believe — and what they cost us to believe them.

These four convictions run through every page of the site, every essay we publish, every client conversation we have. They are not slogans. They are the filter we use to decide which engagements we say yes to, which products we ship under our own name, and which work we walk away from.

AI's biggest leverage isn't doing the same things faster. It's doing things that weren't possible before.

The dominant AI conversation has been almost exclusively about productivity. Faster reports. Faster code. Faster customer service. The problem with productivity-only framing is that it caps the upside at "the same business, but cheaper." Berkeley Haas spent eight months observing knowledge workers using AI and reached a finding that should sit uncomfortably with every transformation roadmap: people who use AI tools don't end up working less — they end up working the same amount, on more things, with the same exhaustion.

The real leverage is somewhere else. It's in the products that didn't previously exist, the workflows that weren't economically viable, the customer experiences that weren't technically feasible. We chase the non-obvious applications because that's where the actual transformation lives. Cost-cutting is table stakes.

The hard part of AI transformation isn't the model. It's the organization around it.

Ninety-three percent of senior data and AI leaders identify human factors as the number one barrier to AI adoption. Only seven percent point to the technology. That number has been stable for two years and is getting worse, not better.

This is not a soft observation. It is the central technical fact of the field right now. Workflow design, adoption, talent strategy, incentive alignment — these are not change-management afterthoughts. They are the actual work. A model deployed into a workplace that hasn't been redesigned around it produces a deck full of pilot results and not much else. We treat the human work as core scope because if we don't, we're just shipping toys into your business.

You can't outsource your AI strategy.

This is the conviction that has cost us the most engagements. The deal we offer is plain: we build with you, not for you. Every engagement is designed to transfer capability — your team owns what we built when we leave. Some buyers want the opposite. They want a vendor who arrives, deploys something, and quietly returns next quarter to deploy something else. That's a recurring revenue model we could probably make work. We have decided not to.

The companies that pull real value out of AI in the next decade will be the ones that built the muscle inside their own organizations. We are an accelerant for that. We are not a substitute.

The frontier moves weekly. Static expertise rots.

The half-life of an AI playbook is now measured in months. A framework that was sharp in March is dull by October. The only credible way to stay current is to be hands-on, building under your own name, shipping things into the world, learning in public.

That's why we operate as a studio rather than a consultancy. We have a portfolio of products we ship under the LeapFactors name. We earn our seat by doing the work, not by reselling last quarter's playbook with a new logo on the cover.

“A model deployed into a workplace that hasn't been redesigned around it produces a deck full of pilot results and not much else.”

About Aaron

Photograph

Founder portrait — Aaron Rutherford. Soft north light from the left, mid-thought. Real desk, real room, no staging.

Worked at

Pilot44 · Petal · Spruce · P&G SharkTank

Education

B.S., Miami University

About Aaron.

Aaron Rutherford is the founder of LeapFactors. He has spent the better part of a decade at the seam between Fortune 50 consumer brands and venture-backed startups — building new products, launching ventures, and watching closely as organizations either absorbed transformative technology or got flattened by it.

He led growth and new ventures at Pilot44, a brand-innovation studio working with P&G, Nestlé, Diageo, Mars, and Hershey. He ran the P&G SharkTank program — five hundred-plus startup evaluations, twenty-five-plus pilots launched, and a front-row education in why most corporate innovation dies in pilot purgatory. Before that he was on the founding team at Petal, a Valar Ventures-backed fintech that nearly hit unicorn status, and at Spruce, an earlier venture-backed consumer startup.

He started LeapFactors because the work he was doing for Fortune 500 brands was the same work that founder-led mid-market companies needed — and almost no one was building a studio for them.

On the work

On AI and the people who do the work.

Every AI rollout we've ever watched closely splits the room into three groups. There are early adopters who are already running. There are skeptics who have watched too many transformations launch with fanfare and quietly die. And there is a much larger middle that hasn't decided yet — that isn't opposed to the work, but hasn't seen what it means for their job, in their context, on a Tuesday at three in the afternoon when they're already behind on three things.

Almost every AI strategy we encounter caters to the first group and dismisses the third. That's why most of them stall. The early adopters were going to adopt anyway. The middle is where the real game is, and the middle is reached through experience, not through slide decks. Nobody's mind has ever been changed by a keynote. Plenty have been changed by fifteen minutes with a tool that made their afternoon easier.

We design for the middle. We treat the workforce as the most important user of every system we ship. We say no to engagements that frame AI as a way to shrink the team. Not because we're naive about cost — every founder we work with cares about the unit economics — but because AI work that doesn't elevate your people doesn't actually transform your business. It just shrinks it. And that's a strategy that wins one quarter and loses the next decade.

What we ship under our own name

The portfolio principle.

We build and ship our own AI products under the LeapFactors name. The first one is the AI Fluency Assessment, a six-factor diagnostic that helps founder-led companies see where they actually are on the AI readiness curve — built around the same diagnostic methodology we use inside paid engagements. Free at the individual level, paid at the org level, privacy-by-architecture in the data model itself.

There will be more. Some will be free, some paid, some will become standalone businesses, some will inform our work with clients. The products will change. The principle won't: we build to prove the craft and to advance the field. A studio that doesn't ship is a consultancy with better business cards.

Filter 01Worldview-aligned
Filter 02Founder-deployed
Filter 03Mid-market relevant
Filter 04Frontier-resistant

Working with us

Working with the studio.

We work three ways: Build (we ship one production system inside your business), Embed (we deploy a forward-deployed pod for three to six months), and Advise (we provide strategy, fractional leadership, and capability programs). Engagements range from a four-week opportunity audit at the entry tier to a multi-quarter studio engagement at the upper tier. Every engagement is senior-only — the person who scopes the work is the person who delivers it.

If you've read this far and the worldview lands, the next step is a thirty-minute call. No pitch deck. We trade notes on what you're working on, and we figure out together whether the studio is the right fit. Sometimes it isn't, and we'll say so.

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