AI advisory & implementation

AI that moves the P&L.

We start with how your business actually works. Then we build the AI that fits it, and stay until your team can run it without us.

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The outside set

Everyone is paddling. Fewer are in position.

In surfing, the outside set breaks further out. Most people miss it because they are sitting inside, taking whatever comes through.

AI is the same. The frontier throws off a new model every week, and almost none of it will move your business this quarter.

The work is choosing which wave you want, then being in the right place when it arrives.

Most AI investment isn’t paying off

Spending is up. Returns mostly are not.

of leaders report having established ROI from AI

61%

of CEOs say their board is rushing AI transformation

11%

of CEOs say AI’s impact is linked to financial reporting and reviewed regularly

Across the research the blockers are consistent, and they are rarely talent or technology. They are integration, adoption, and measurement.

The companies getting a return tend to be the ones keeping score. KPMG found organizations with full visibility into their AI operating costs were five times more likely to report established ROI, 15% against 3%.

Sources: KPMG Global AI Pulse, Q2 2026 (fielded April–May 2026; 2,145 senior leaders, 20 markets) · BCG, Split Decisions: The CEOs and Boards Survey (fielded March 2026; 351 CEOs and 274 board members at companies with $100M+ revenue, 76% private) · EY CEO Outlook (fielded March–April 2026; 1,200 CEOs, 21 countries). Self-reported executive survey data.

Why the usual options stall

Three familiar options, each with a predictable weakness.

We built OutsideSet because none of them brings both halves: the judgment to choose the right problem and the ability to build the answer.

The big consulting firm

Strategy houses and global integrators

Strong on the thesis, thin on delivery. The team that sold you isn’t the team that shows up, and the economics rarely pencil for a company your size. You get frameworks; you don’t get working software.

The dev shop

Boutique AI firms, offshore teams, freelancers

They build exactly what you spec. The hard part is knowing what to spec, and no one on that side is measuring whether it moved a number the business cares about.

The vendor channel

Platform partners and preferred suppliers

Advice that comes bundled with a stack. The recommendation is shaped by what the provider sells, which means model lock-in and vendor lock-in before you’ve proven anything.

We sit in the middle: consulting rigor and hands-on build in one senior team, where the people who sell the work are the people who do it.

How we work

Diagnose. Build. Run.

Three stages, each earning the right to the next. We never ask for a large commitment up front.

Diagnose

2–3 weeks · fixed fee

We map where AI can move your numbers, size it in dollars, and read your real conditions: data, systems, processes, and people. You end with a ranked roadmap and an honest go / no-go.

Build

6–12 weeks · fixed or value-based

We build the highest-impact use case and put it into production on live data, used by real people, instrumented against a metric you already track. Senior builders, constrained scope, working software.

Run

Ongoing · monthly

Anything deployed decays. Accuracy drifts, systems change, models move monthly. We monitor, tune, and extend what we built, and report performance against the metric it was built to move.

We work at a pace the organization can absorb. Adoption is usually what decides whether the work shows up in the numbers, and change that outruns the people doing it tends to get dropped. Some teams want us to lead and build fluency from the ground up. Others want a partner in the trenches. Either way, the test we hold ourselves to is whether it is still running after we go.

Where we start

One fixed-fee diagnostic. Low risk, high clarity.

Two to three weeks, a price agreed before we begin, and one plan your board and your management team can both put their name to.

What you get

A value map of where AI can move your business, sized in dollars rather than theory
A current-state read on your data, processes, and organizational readiness
Use cases ranked by impact and feasibility, against your actual conditions
A build spec for the first one, with success metrics leadership can track
A go / no-go recommendation with an honest risk assessment

Slope, not score.

We look at how fast you are climbing, not only where you sit today. The floor keeps rising, so what counted as capable a year ago is fairly ordinary now. Over a few years, trajectory tends to be more informative than a snapshot.

For the board

A quantified opportunity, sized and sequenced, with metrics they can track. Ambition grounded in what this company can actually deliver, rather than in what the headlines promise.

For the management team

A roadmap your people can actually execute, scoped to prove value without disrupting the business while it runs, and a credible answer when the board asks what is being done.

Why OutsideSet

Practical AI leading to real value.

Practitioners, not advisors

Senior operators who have built and shipped, not only advised. The people in the room are the people doing the work.

Model-agnostic, conflict-free

The right tool for the problem, whether that is commercial, open source, or nothing at all. We don’t resell a stack, so there is no lock-in and no conflicted advice.

Fixed fee, never hourly

You know the number before we start, and the scope is written down. We would rather share risk on the outcome than meter hours.

Evidence over opinion

We score what we observe rather than what we are told, and we agree the baseline before the work starts. Without an agreed starting number, the result at the end is hard to read.

Signal, not noise

The frontier throws off a new model and a new reason to start over every week, and almost none of it is actionable this quarter. We work with what’s proven, and let the rest prove itself first.

A pace that holds

Starting quickly and moving at a sustainable rate are not in conflict. In practice, change that outruns the people doing the work is the kind that gets dropped.

Our point of view

Why we exist

I spent years watching both sides of this. Startups moved fast but rarely understood the industries they were trying to change. Enterprises had the ambition but couldn’t turn it into results. Someone needed to bridge the two: consulting judgment and hands-on build in the same people. That is why OutsideSet exists.

We are less interested in the newest thing than in the thing that works: in production, on your data, run by your people. That usually means proven technology pointed at a problem worth solving, and leaving the rest alone until it is ready.

The expertise that matters most already exists inside your walls. We’re here to combine it with AI, not replace it.

Why now

One of the harder gaps in this is not technical. It sits between the boardroom and the management team. Around 61% of CEOs say their board is rushing AI transformation, and more than a third say their board overestimates what AI can replace rather than where it can realistically augment their people.

Boards are not wrong to push. They are being asked to judge a technology that changes monthly, and among directors unsure of their own AI knowledge, 40% say their organization is moving too slowly. BCG calls it board FOMO. The pattern that tends to follow is urgency without a grounded view of what is actually buildable, which is where most stalled pilots start.

Both sides are after the same outcome. Boards want business cases and ambition. CEOs want an honest read on what the technology can deliver today, and a number of them said outright that they want outside help where the competence is not in house. What closes that gap is usually a single plan: ambitious enough for the board to back, grounded enough for management to deliver.

The bar for starting is lower than it looks. A transformation program and a new platform are not prerequisites. One workflow in production, moving a number you already track, with the measurement agreed up front, is enough to settle the argument either way. That is a two-to-three week decision rather than a two-year one.

Board and CEO figures from BCG, Split Decisions: The CEOs and Boards Survey, fielded March 2026: 351 CEOs and 274 board members at companies with $100M+ in annual revenue, 76% of them private.

Leadership

Who you would be working with.

Hans Yang

Founder

Hans has spent his career on both sides of the table. He has founded and run companies and shipped products used by millions, and he has led digital transformation for the Fortune 500 from the consulting side. How OutsideSet works comes straight out of that combination.

Boston Consulting Group — Partner, digital transformation for Fortune 500 clients; corporate venture, 10+ companies from concept to Series A
Microsoft — VP, Startups; $1B+ revenue motion across a 600-person organization
Zynga — Studio Head; founded the LA studio, $100M run rate, 48M users
Luxe Valet — COO; acquired by Volvo
MIT, BS Engineering · UCLA Anderson, MBA

Behind Hans, a vetted bench. For every engagement we assemble a small team of senior practitioners: strategists, engineers, and domain specialists matched to the work at hand. You get the right expertise at the right moment, without paying for a large firm’s idle capacity.

Work with us

Start with a conversation.

Tell us where you are and what you’re trying to solve. If there’s a fit, we’ll propose a scoped diagnostic with a fixed price. If there isn’t, we’ll tell you that too.

Prefer to just grab time?
Book 30 minutes →

hans@outsideset.ai