A mid-market PE firm deployed PDS across a $48M commercial HVAC platform. 12 weeks of implementation. $110K total cost. $15.3M added to the projected exit valuation.
The Players
The PE Firm
Ridgecrest Capital Partners
Mid-market PE firm, $2.8B AUM, 14 portfolio companies in Fund III. Hired their first Technology Operating Partner with a $500K annual budget to deploy AI across the portfolio before exits.
The Portfolio Company
Apex Mechanical Services (Illustrative Example)
$48M commercial HVAC & plumbing platform. 8 locations across AZ, NV, NM. 310 employees. Grown from $22M through 3 add-on acquisitions. Target exit: 8–9x EBITDA in 18–24 months.
The Problem
Growth through acquisitions had created a patchwork operation. The company was generating $48M in revenue but losing a significant portion to operational gaps no one had bandwidth to fix.
28% of inbound calls abandoned
Sent to voicemail or an answering service that booked appointments only 31% of the time. ~340 missed new-customer calls per month = $952K in monthly revenue exposure.
4.2-day average lead response time
Industry best practice is under 1 hour. A property manager with a 200-unit complex called after hours — by morning they had booked a competitor. Estimated lost revenue: $41,000 from one call.
Sales team wasting 40% of their time
55% of inbound leads were unqualified — residential callers, out-of-area, tire kickers. The 6-person commercial team was doing manual lead triage instead of closing deals.
Manual dispatch across 8 locations
Office managers spending 2–3 hours per day manually scheduling technicians in ServiceTitan. Wrong-skilled techs dispatched to jobs. Scheduling gaps costing billable hours.
Phase 1 · 30-45 Days · $15K
PDS conducted a deep operational audit — not a technology audit. The goal: find where the business loses money, misses revenue, or wastes labor hours, then map each problem to an AI solution with a projected financial impact.
Discovery & Data Collection
Transcribed 2 weeks of RingCentral call recordings using Deepgram. Classified 4,218 calls by type. Spent a full day observing CSR workflows at Phoenix HQ. Reviewed 90 days of Salesforce pipeline data.
Opportunity Mapping & ROI Modeling
Built a detailed opportunity matrix mapping each AI use case to a projected financial impact — grounded in actual data, not industry benchmarks. Every number had a confidence rating and complexity score.
IC-Ready Deliverable
Delivered a 32-page AI Readiness Assessment formatted for investment committee review — including sensitivity analysis, implementation risk factors, and a projected aggregate EBITDA impact of $1.4M–$2.1M annually.
The Moment That Closed the Deal
During the presentation, Ronald played a recording of one missed after-hours call. A property manager with a 200-unit apartment complex needed emergency HVAC service for 14 units. The answering service told them someone would call back in the morning. By morning, they had booked a competitor. Estimated lost revenue from that single call: $41,000. David approved the full implementation engagement that afternoon.
Phase 2 · 12 Weeks · $95K
Sprint 1 · Weeks 1–4
24/7 AI Voice Agent
Deployed across all 8 locations, integrated with ServiceTitan and RingCentral. The agent handles after-hours calls, overflow during business hours, and first-ring pickup. Books directly into ServiceTitan in real time, handles emergency triage, answers FAQs, and sends automated text confirmations.
Sprint 2 · Weeks 5–8
Scheduling Automation + Lead Qualification
Built an n8n scheduling engine that auto-slots appointments from voice, web, and email into ServiceTitan based on technician skills, location, and availability. Added an AI lead qualification layer to Salesforce — hot leads routed instantly to sales reps with a full dossier. 2 of 3 CSRs redeployed into revenue-generating roles.
Sprint 3 · Weeks 9–12
PE Performance Dashboard + Optimization
Built a real-time dashboard for the operating partner and portfolio CEO showing AI performance tied directly to financial outcomes — not vanity metrics. Every number connects to EBITDA. Added a post-service review workflow routing happy customers to Google reviews and unhappy customers to the Customer Success Coordinator.
Phase 3 · Results at 6 Months
| Metric | Before | After | Impact |
|---|---|---|---|
| Inbound call answer rate | 72% | 98.4% | +26.4% |
| After-hours booking rate | 31% | 71% | +129% |
| Monthly AI-booked revenue | $0 tracked | $127K/mo | +$127K/mo |
| Avg. commercial lead response | 4.2 days | 11 minutes | −99.8% |
| Sales qualified lead ratio | 45% | 78% | +73% |
| Answering service cost | $24K/year | $0 | −100% |
| CSR admin labor | $135K/year | $45K/year | −$90K/yr |
| Google review average | 3.6 stars | 4.4 stars | +0.8 |
The Exit Valuation Math
EBITDA Before PDS
$5.8M
Projected EBITDA After
$7.6M
Exit Value Added (8.5x)
+$15.3M
Total PDS Engagement Cost
$110,000 (audit + implementation)
Return on AI Investment
139x
What Happened Next
| AI Readiness Assessments (7 × $15K) | $105,000 |
| Implementation Sprints (4 completed × avg. $95K) | $380,000 |
| Implementation Sprints (3 in progress, partial) | $142,500 |
| Managed AI Services (4 companies × avg. $8K/mo) | $160,000 |
| Total Year 1 from One PE Firm | $787,500 |
Engagement Summary
Tech Stack
Start with a $15K AI Readiness Assessment. 30-45 days. One portfolio company. A prioritized roadmap with projected EBITDA impact — formatted for your investment committee.
No commitment required. NDA available on request.