OptimEyed

Add AI value now. Be exit-ready when it counts.

OptimEyed builds AI into the workflows that drive your EBITDA, measures it the way a buyer will, and gets your numbers and data room ready for diligence. For owner-led and PE-backed lower-middle-market companies.

Book a call See what we do
Exit readiness board · Month 6 Example data
Buyer-ready 3/5 In progress 1 Flagged 1
WorkstreamDay 1NowStatus
Month-end close19 days6 days ✓ Buyer-ready
AI workflow: AP invoice matchingManual91% touchless ✓ Measured
EBITDA add-backs documented3 of 1111 of 11 ✓ Buyer-ready
Data room indexedNone84% In progress
Customer concentrationTop 3 = 41%Top 3 = 38% ⚠ Buyer will ask
Month-end close
19 days → 6 days
✓ Buyer-ready
AI: AP invoice matching
Manual → 91% touchless
✓ Measured
Add-backs documented
3 of 11 → 11 of 11
✓ Buyer-ready
Data room indexed
None → 84%
In progress
Customer concentration
Top 3 = 41% → 38%
⚠ Buyer will ask
The problem

Buyers only pay for what they can verify

Most companies are doing AI and planning an exit as two separate projects. The buyer sees them as one question: is this EBITDA real, and will it hold up after close?

AI value nobody can audit

Pilots that save "hours" but never show up in EBITDA, because nobody set a baseline or agreed on a dollar formula.

Numbers rebuilt by hand

A close that takes weeks, KPIs pulled together in spreadsheets, add-backs nobody wrote down. Every gap becomes a diligence question.

Surprises found by the buyer

Issues the buyer's team finds first turn into price cuts, escrows and earn-outs. The same issues found early are just a to-do list.

Same claimed savingsIn diligence
"AI saved us time," no baselineDiscounted
Savings from a one-off spreadsheetQuestioned
Run-rate measured vs. Day-1 baseline, formula shownUnderwritten
Hours saved only count when they're redeployed. That's the rule we measure by.
What we do

One engagement, two payoffs

The work that adds EBITDA now is the same work that makes it believable to a buyer later. We do both, in that order.

01

AI value

Now · in the workflows that drive EBITDA
  • Finance operations. Faster month-end close, touchless AP invoice matching, and collections workflows that compress DSO.
  • Revenue leakage. Billing denials root-caused, eligibility and pricing checked automatically, quotes turned around faster.
  • Frontline operations. Tickets and inbound requests triaged and drafted, no-shows reduced, churn risk flagged before it hits revenue.
  • KPI packs. Monthly management reporting built from your own systems, with drafted variance commentary instead of a week of spreadsheets.
02

Exit readiness

12–24 months before a sale or recap
  • Buyer's-eye red-flag scan. The same first pass a buyer's diligence team will run, done early, with every finding turned into an owned fix.
  • AI value in the buyer's language. Run-rate impact against a Day-1 baseline, with the formula shown, so it can be underwritten.
  • Numbers that hold up. KPI history, add-back support and a repeatable close, so your QoE provider and advisors start from clean files.
  • An indexed data room. Documents organized and cross-referenced before the first buyer asks, not assembled in a panic after the LOI.
How it works

Small first step, measured every step after

No long transformation program. Each step ends with a number and a decision.

2 weeks

Diagnostic

Map 3–5 friction workflows, score them in dollars, and run a first readiness scan. The fee is credited against the pilot if you go ahead.

6–8 weeks

Pilot

Ship the highest-value workflow into daily use, measured against the Day-1 baseline. 20% of the fee rides on hitting the agreed target.

Monthly

Value & readiness retainer

Roll out the next workflows and keep the readiness board moving until you go to market. 3-month minimum, then 30 days' notice.

Example: one workflow, start to finish

Optometry: benefits verified overnight

Simulation · example data

Eye care practices hand-check every patient's vision benefits on the insurer portals each morning. The fix: run it overnight, flag exceptions instead of guessing, then measure what it does to capture rate and average sale. Run the batch yourself.

Checked 0/8 Flagged for staff 0 Staff minutes saved 0
ApptPatientPlanExam copayFrame allow.CL allow.Status
Why it matters for value

The automation is the easy part. The scorecard is what a buyer underwrites.

  • Baseline first. Four numbers before anything changed: % of schedule verified, capture rate, average complete pair, walkouts recovered.
  • Then the operations work. The sheet in the optician's hand before the patient sits down, a real handoff script, a 48-hour walkout follow-up.
  • Then the proof. The same four metrics every Monday against the practice's own baseline. That history is what goes in the data room.
Who's behind this

I've sat on the buyer's side of the table for 75+ closed acquisitions. I know what diligence discounts, and what it pays for. Now I build the AI that adds the value, and the evidence that proves it.

75+ deals closed

8+ years of corp dev and valuation. Closed 75+ acquisitions inside MyEyeDr. (a Goldman Sachs portfolio company) and helped add about $350MM of revenue to PE-backed healthcare platforms, including a ~$100MM, 25+ location deal from pre-LOI to APA.

AI already in production

At a PE-backed specialty veterinary platform, built an M&A pipeline platform on HubSpot, SQL and AI that replaced manual Excel reporting across the sponsor's whole portfolio.

I build it myself

Investment-banking valuation training plus hands-on Python, SQL and modern AI. No junior team, no offshore handoff: the person who scopes the workflow ships it.

Peter Burrus, OptimEyed

Next step

A 30-minute call on one workflow and your exit timeline

Tell me about the company and I'll follow up to schedule it.

Prefer email? peterburrusjr@gmail.com