We agree the metrics first
Before launch we define the handful of numbers that matter: response time, qualification rate, booked appointments, show rate and follow-up completion.
These pages are example workflows, not client results. They show the business types we work with, the manual problems we see, and exactly how we would build the system — so you can picture it on your own pipeline.
We deliberately do not publish a portfolio of client outcomes here. Real results belong to the businesses that earned them, and we only share measurable numbers when we have that client’s written permission and verified data behind them. What we can show you honestly is the thinking: how we diagnose a manual workflow, which layers we would build, and what we would measure once it is live.
Each scenario below follows the same shape — the business type, the manual problem, the system we would build, and what we would track. Read it as a proposal template for your industry, not as a claim about anyone else’s results.
Illustrative scenario. We publish measurable results only when we have client permission and verified data. Everything on these pages describes a proposed workflow, not an outcome we achieved.
Pick the one closest to how your business actually runs.
AI intake for an HVAC company — no-cool and no-heat calls, tune-ups, maintenance agreements, SEER2 replacement quotes and dispatch.
AI dispatch for a plumbing company — burst pipes, water heaters, drains, repipes and sewer lines routed to the right tech.
AI intake for a roofing company — storm damage, inspections, estimates, insurance claims and tarping requests.
AI reception for a dental practice — scheduling and admin only: new-patient exams, hygiene recall, insurance verification and reminders.
AI follow-up for real estate leads — buyer and seller leads, showings, lead ads and drip follow-up.
AI booking for an online coach — discovery calls, an application funnel, webinars and no-show recovery.
Instagram DM sales for a small business — comment-to-DM, DM follow-up, link-in-bio and booked calls.
When a system goes live, we agree on what we will measure — and we only publish it with permission.
Before launch we define the handful of numbers that matter: response time, qualification rate, booked appointments, show rate and follow-up completion.
Numbers come from your CRM, calendar and conversation records — not from estimates, screenshots or a marketing narrative.
If a result is worth sharing, we ask the client for written permission and verify the data with them first. No permission, no publication.
Worked examples are marked as illustrative scenarios, exactly like the pages in this section. We never dress up a hypothetical as a case study.
“The agent replies instantly” is a description of the build. “It produced more revenue” is an outcome that needs proof. We keep the two apart.
Sometimes the fastest win is not automation. If that is true for you, an honest audit should say so rather than sell a build.
Illustrative scenario. We publish measurable results only when we have client permission and verified data.
Whichever scenario fits you, the engagement runs the same four stages.
We map how leads arrive today and find the single biggest leak in the journey.
We configure the capture, response, qualification and follow-up layers on your tools.
You approve the knowledge base and escalation rules, then the system goes live.
We review the agreed metrics together and tune the system over time.
Timelines vary by scope. We confirm dates after the audit — no fixed promises.
Tell us how leads and follow-up work today. On a free strategy call we will map the fastest fix for your situation — often the first automation worth building.
Illustrative scenario. We publish measurable results only when we have client permission and verified data.
Book a free AI strategy call and we will walk the scenario that fits you against your live pipeline.