EI × AI Advisory
You're 15 people doing the work of 40, and everyone says AI is the answer. It is — but only if it's installed into a team that's built to absorb it. We diagnose how yours actually operates, then build the systems your people will use instead of quietly ignoring.
Built on proprietary models and frameworks tailored to your needs · Teams of any size
The gap we close
At 5 people, everyone does everything and the tools don't matter. At 25, the seams show — and AI dropped onto a team with unaddressed friction doesn't fix the friction. It automates it. Faster mess, same mess.
We hold both. Our proprietary models and frameworks are tailored to your needs, reading how your team actually operates — so we know what will break before we build. It tells us where adoption fails; applied AI builds the thing that sticks.
What we do
Structured, time-boxed engagements. The deliverable is a working capability — rubrics, workflows, adoption plans — not a slide deck.
Core / A
A two-week structured assessment of how your team actually runs — where decisions stall, where hours disappear, and who will resist versus who simply can't yet. You get current state, goal state, and the roadmap between them, including which AI moves your numbers and which is theater.
Core / B
Redesign of the workflows where AI actually saves hours — client follow-up, intake, reporting, the admin drag that eats your week. Built against the tools you already pay for, not a new stack you have to learn.
Core / C
Role clarity, decision rights, and capability gaps mapped before you hire into the wrong shape. The structural work that decides whether your next five people compound the team or complicate it.
Core / D
Documentation your team keeps and uses, coaching through the first real cycle on the new system, and a close-out that reports against the numbers we baselined in week one.
How an engagement runs
Standardized so the work is repeatable and the outcome is predictable — roughly a three-month arc for core engagements.
PHASE 01
Weeks 1–2Baseline the current state — hours lost to admin, decision cycle time, turnover cost, and adoption risk. Map team dynamics against proprietary models and frameworks tailored to your needs and define what success actually measures.
PHASE 02
Weeks 3–9Build the AI workflows against your real stack. Weekly working sessions and 1:1 coaching iterate the systems against actual use, so the team shapes the tool instead of receiving it.
PHASE 03
Weeks 10–12Adoption plan, documentation your team keeps, and an executive close-out that quantifies the impact in the metrics we baselined on day one.
Who leads the work
Five industries of hard-won experience — healthcare, real estate, federal contracting, corporate enterprise, and small business — distilled into one operating model. Five very different playbooks, one approach. Add five years working hands-on with AI, well ahead of the curve, and the result is simple: AI used as a business tool, in the places it actually moves your numbers.
20+ yrs
Building teams and scaling businesses
5 industries
Healthcare · Real estate · Federal contracting · Corporate · Small business
5 yrs in AI
Hands-on practice since before it was table stakes
One model
Five playbooks distilled into a single operating approach
Practical by design
AI treated as a business tool with measurable returns — not a science project
Proof
Every engagement baselines its numbers in week one and reports against them at close. The figures below are the targets we build toward and measure against.
Target outcome
6–9 hrs
Reclaimed per person, per week
Admin and follow-up workflows rebuilt around where AI actually saves time.
Target outcome
2×
Decision speed
Role clarity and decision rights mapped before the tooling goes in.
Target outcome
91%
Tool adoption at 90 days
Change plan and 1:1 coaching run alongside the build, not bolted on after handoff.
Target outcome
−38%
Time-to-fill
Structured screening and AI-assisted sourcing applied to the hiring pipeline.
Target outcome
−26%
Cost-per-hire
Fewer wasted cycles on the wrong candidates and the wrong steps.
Target outcome
2 wks
To a working roadmap
Current state, goal state, and the sequence between them — before any build starts.
“We'd bought the tools twice already. This was the first time anyone dealt with why our team wouldn't touch them.”
“The diagnostic named the friction we'd been working around for two years. Seeing it written down changed the conversation.”
“My team got hours back every week without feeling like the tool was auditing them. That balance was the whole trick.”
“We stopped debating which platform to buy and started fixing how decisions actually moved through the team.”
“The rubrics gave us something we could actually defend in a debrief. Internal arguments got shorter and better.”
“Every previous consultant handed us a deck. This one handed us workflows the team was already using by week six.”
“Knowing who couldn't yet versus who wouldn't changed how we coached people. That distinction alone was worth it.”
“We were 14 people doing the work of 40. The build didn't add headcount — it gave us back the week.”
“The close-out reported against the same numbers we baselined on day one. No hand-waving about impact.”
“Role clarity came before the tooling, and that's why the tooling stuck. We'd have done it backwards on our own.”
“Adoption didn't fall off after handoff, which is the first time that's ever been true here.”
“It was practical the whole way through. Nothing felt like a science project, everything tied to a number.”
Start with a diagnostic
The diagnostic surfaces your real numbers and the friction hiding underneath them. It's the fastest way to know whether a full engagement is worth it before you commit to one.
Typical first conversation: 30 minutes. No pitch — a scoping of the problem.