← All case studiesHVAC · Done-For-You AI System · Unchained From Agencies
They burned $14K on agencies. Then we built them a system they own.
AirCentral burned $14K across three agencies - a LinkedIn VA, a cold email shop, trade association memberships - and got zero pipeline. Deep-Y replaced the entire agency layer with infrastructure they own: signal feeds, deliverability, personalization, reply routing. First contract signed on day 18. $540K in 90 days.
$540K
Signed Pipeline / 90 Days
89%
Email Open Rate
340
Commercial Meetings Booked
12
Contracts Signed
They had already paid the agencies. The LinkedIn VA who found zero deals in two months. The cold email agency that sent 10,000 emails and booked one meeting - which didn't show. The trade association memberships that cost $14K and produced one inbound lead. Every agency took the budget and blamed the market. Nobody built anything AirCentral could keep. We did. A system they own. $540K in 90 days.
Day 1
ICP and signal sources defined
2,800 target accounts
Day 30
Infrastructure live, first sends
14,000 emails sent at 89% open rate
Day 60
First contract signed
$38K chiller replacement
Day 90
Pipeline filled
$540K in signed pipeline from 340 booked meetings
Before the System / After the System
The ceiling wasn't their service. It was the absence of a system watching the right signals.
2 Years
$4K avg
Residential jobs. Same competitors. Price war every week.
Deep-Y didn't optimize AirCentral's outreach. We replaced the manual layer entirely - building the signal pipeline, the deliverability infrastructure, and the reply routing that turned permit filings into signed contracts.
The Challenge
Two years. Three agencies. Zero pipeline.
Before Deep-Y
$14K burned · 0 deals
A LinkedIn VA. A cold-email agency that sent 10,000 generic emails for 1 no-show. Two trade-association sponsorships. Every retainer blamed "market conditions" and disappeared.
After Deep-Y
$540K signed · 90 days
A signal-driven outreach system AirCentral owns: 6 sending domains, permit-filing triggers, AI personalization, AI reply triage. No retainer to keep it running.
Commercial HVAC buyers act on specific signals: permits filed, tenant departures, management changes, equipment-age thresholds. Generic outreach never sees them. Relevance does - and relevance requires a system watching those signals in real time.
Day 18
First commercial contract signed. 4 sending domains warmed in 21 days · permit-filing triggers as subject hooks · AI reply triage routing replies straight to the calendar.
89% open rate - permission-grade deliverability
89%
Commercial procurement inboxes reject generic mass sends on contact. We used permit-filing signals as subject-line hooks ("Saw the filing for 420 W Main..."), built 6 clean sending domains warmed over 21 days, and kept AirCentral's legacy domain completely isolated. Every open was structurally earned - not luck, infrastructure.
"We burned $14K on agencies that took our money, sent thousands of generic emails, and disappeared. Deep-Y built a system we actually own - signal feeds, deliverability, sequencing, all of it. $540K in 90 days with no new headcount. It still runs. Nobody's billing us a retainer to keep it alive."
AC
AirCentral
Commercial HVAC · US market
The Approach
How we built the system AirCentral now owns
Deep-Y is not a campaign agency. We built every layer - signal sources, ICP, infrastructure, personalization, sequencing, qualification, and handoff - and handed it over to run in AirCentral's name. No retainer required to keep it running. No dependency. AirCentral's team did not write a single email.
Deliverability System
$540K Pipeline
01
Commercial ICP from scratch
Built ICP filters on building size (50K-500K sqft), HVAC age (7+ years), and ownership changes. 2,800 target accounts across the metro - none from Apollo.
02
Signal sources nobody watches
Wired permit filings, tenant departures, and management company changes into a live feed. These signals don't exist in standard data vendors - we built the pipeline from public records.
03
Deliverability infrastructure
6 sending domains, 21-day warm-up, inbox rotation. AirCentral's legacy domain was never touched. Result: 89% open rate across 14,000 sends with zero complaints.
04
AI-written, signal-grounded personalization
Every email referenced the specific trigger: "Saw the permit filing for 420 W Main..." AI generated each message from signal data. No templates, no merge tags - structurally custom per recipient.
05
Meeting-booking auto-loop
AI triage routed interested replies straight to AirCentral's calendar. 340 meetings booked in 90 days, 78% show rate - zero human inbox management.
06
Weekly compounding loop
Every Friday: underperforming angles retired, new signals added, ICP refined from closed-deal data. Month 2 outperformed month 1 by 40%.
Under the Hood
How the system was built - step by step
The AirCentral AI outreach system had six components, each solving a specific failure mode in their previous manual outreach.
01
Domain architecture (week 1)
Built 4 sending domains with proper SPF, DKIM, and DMARC authentication. AirCentral's primary domain was excluded from cold sending to protect deliverability of existing client communications. Each sending domain was aged 30+ days before first use.
02
ICP signal model (week 1)
Mapped the commercial HVAC buyer signals: facility manager job titles, building square footage data, recent construction permits, and LinkedIn job-change events indicating new facility managers. Built a scoring model that ranked 3,400 target accounts by buying probability.
03
AI personalization engine (week 2)
Trained the AI on 40 real conversations from AirCentral's past deals to understand the language their buyers responded to. Each email referenced a specific signal about the prospect's building or recent activity - not generic personalization tokens.
04
Warm-up and ramp protocol (weeks 2-3)
Started at 8 emails/day per domain, increasing by 5 per day over 21 days to reach full volume. Monitored sender reputation scores daily. Achieved 89% open rate before any sequence optimization was needed - a deliverability baseline.
05
Reply handling and routing (week 3)
Built an AI reply classifier that sorted responses into: interested (routed to AirCentral sales), not now (scheduled follow-up at 60 days), referral (extracted new contact), and objection (fed into sequence optimization). 340 interested replies were routed without a human touching the inbox.
06
Optimization loop (ongoing)
Every Friday: AI analyzed the week's reply patterns, updated subject line variants, and reweighted the signal model based on which prospect types converted. By month 3, conversion rate from email to meeting had improved 40% over the baseline.
The Result
The 90-day scoreboard
Signed commercial contracts12 contracts, $540K total pipeline
Average deal size$45K (vs $4K residential)
Email open rate89% (vs 20% industry average)
Reply rate24% across 14,000 sends
Commercial meetings booked340 in 90 days
Meeting show-up rate78%
Cost per qualified lead$0.80
First contract closedDay 18 from launch
ROI on Deep-Y engagement4.2x in the first 90 days
New headcount requiredZero
$540K signed in 90 days. 12 contracts averaging $45K each - against $4K residential jobs. The system runs in AirCentral's name, on their domains, with no retainer keeping it alive. Commercial revenue now grows faster than residential ever did.
The system in motion · AI outreach running on AirCentral domains
Video AI System · Layer 2
1,253 videos. 6 months. Zero video crew.
After the outreach system proved the commercial market, we layered in a Video AI System. Scripts generated, videos produced, distributed across platforms - same client, second system, revenue story amplified without adding headcount.
Videos produced1,253 in 6 months
Video team requiredZero
Systems running simultaneouslyOutreach + Video
Additional headcountNone
This is what compounding looks like. The outreach system built the pipeline. The video system built the brand. Both ran simultaneously. Neither required AirCentral to hire.
There's a ceiling in your pipeline because nobody's watching the right signals yet.
We'll identify the exact signal sources, infrastructure gaps, and ICP definition that's keeping you in the wrong market - then show you the system that changes it.
