A practical framework for identifying which workflows are worth automating, what should stay human, and how to move from AI experiments to implementation you can measure.
Live · 75 minutes · with Q&A at the end
You've already heard about agents, copilots, voice agents, automations and "AI employees." What's missing is the part nobody answers:
"Where exactly should AI go in my business?"
"What do we automate first — and why that instead of something else?"
"Will it make money, or just make activity?"
"Will the team actually use it, or work around it?"
"Do we need developers? An AI department?"
"How do I know whether the implementation actually worked?"
The same model everyone else uses produces different results depending on what it's connected to. You'll see the whole anatomy: model + context + business data + tools + workflow + human decision points. Without that chain, AI just produces text.
You don't have to become the engineer. You own the outcome, the constraints, the approvals and the economics. Architecture, integration and testing belong to someone else. You'll see exactly where that line goes — and what breaks when it moves.
Nobody's systems are clean. The way out isn't a giant transformation — it's one bounded workflow: input, output, owner, systems, human checkpoints, and one success metric. Build, launch, observe, improve — and only then decide whether expanding makes economic sense.
A lending branch network. It isn't our only implementation and it doesn't define the company — it's a clean example of the same mechanism taught in the session.
Customers who had already paid off their loan, asleep in the CRM. Nobody at the branch had time to dial them.
One bounded process: pull paid-off customers from the CRM, reach them, qualify interest, hand only the interested ones to a person.
Orchestration, a voice agent, and a live transfer to the branch. With calling hours, scripts and human checkpoints.
13,159 calls in 14 days · 224 live transfers · the pilot went from 10 to 28 branches.
Nobody on the team dials a number. The branch only picks up when there's already an interested customer on the line.
Real numbers from a pilot that's still running — not a projection. See the full case →
PTS AI installs and operates AI-assisted revenue systems for multi-branch companies — the layer between "a lead comes in" and "a human closes." Live operations across lending branch networks and tax preparation. This session is the framework we use internally to decide what to build first, not a trends talk.
You have customers, prospects, processes or operational data already moving every day.
Someone on your team does repetitive work that decides whether revenue lands or leaks.
You can approve a bounded experiment without asking a committee.
You want judgment to decide with — not another tool demo.
You don't have customers or a working sales process yet.
You're looking for a prompting course or a tool list.
You expect AI to replace your team. That's not what we're teaching.
You want a full company transformation in 90 days.
No cost. We send you the link and one reminder before it starts.
The link is on its way by email. If you want to arrive ahead: think of one process in your business that repeats every week and today depends on someone remembering.