AI that frees your people
and grows your business.

Most AI consultants have never run a business. Scott has. He delivered AI at Fortune 100s through Accenture, then left to become an operator at Tumble — where he and his team shipped roughly a dozen agents in production. Clarified is the firm he wished existed when he was the one doing the hiring.

Practically: no slide decks, no frameworks, no army of junior consultants. Scott shows up. He looks at your business. He builds things, or tells you not to.

We will never sell you on AI as a way to shrink your team. That isn't how we think about this work, and it isn't how we did it at Tumble.

We follow Bob Chapman's Truly Human Leadership philosophy from Barry-Wehmiller: a business is measured by the way it touches the lives of the people in it. AI, done well, makes those people more capable, more valued, and freer to do the work that actually matters. We will help you use it to make your team — and your business — bigger in the ways that count.

Your team probably already does, at least a little. ChatGPT is a glimpse of what's possible — it isn't a process that runs your business.

The work we do is the gap between a cool demo and a system that handles real customer intake, real quoting, real dispatch, every day, inside your stack, with your data, integrated with your tools. That's a different problem and it's the one most companies get stuck on.

Pricing depends on what we find together. As a market reference point, most first-year AI implementations for $1M–$50M businesses land somewhere in the $20k–$75k range; ambitious platform-shaped builds run higher. Those are industry norms, not Clarified quotes — the real number depends on what we find in your business.

The first call is always free. Let's figure out if there's a fit before anyone commits to a number.

Workflow fixes — things like a concierge layer, an agentic quote desk, or field-service triage — typically land in 4–10 weeks. Bigger agentic builds (the ones that unlock a new capability rather than clean up an existing one) run 8–16 weeks for a first version, and often continue from there.

The first conversation is free, and scoping the timeline is one of the first things we'll do together.

AI systems make mistakes. So do people. The question is whether the system catches them, and whether the cost of a mistake is bounded.

We design the workflows we build for this from day one — confidence thresholds, human review where it matters, escalation paths, audit trails. The result is a system you can trust because you understand what it can and can't do, not because it claims to be perfect.

That's what we hear most — and it's not a reason to wait. Scott doesn't just plug AI into an existing stack. He builds the stack, or the pieces of it that are missing, as part of the engagement. CRM cleanup, data pipes, knowledge bases, integrations, the AI agents on top of all of it.

If you've got a modern stack, we'll meet it where it is. If you've got a spreadsheet and a Gmail inbox, we'll build what's missing alongside you. Either way, you end up owning a system that runs the business with AI in it — not a slide deck about what you could do if you were ready.

The cleanest single metric is revenue per employee. If that number is going up over time, the AI is earning its keep. If it's flat while revenue grows, the business is scaling human labor wearing an AI coat — and we'll tell you so.

There is a trap where revenue goes up because headcount went up, not because AI took on more of the work. We build our engagements so that trap is visible in the numbers, and we'll flag it the moment we see it.

No. We're based in San Francisco and we work with operators anywhere. Most of the work is remote; we travel for the engagements that need it.