40% Reply Rate. 20+ Booked Calls. Zero Manual Prospecting.

Ovrhaul builds and distributes AI-native applications — including ChatGPT Apps and Claude Connectors — that connect brands to 900M+ weekly users on leading AI platforms. They work with global agencies and brands to develop production-grade AI apps, guide them to market, and support long-term growth in an agentic commerce world.

Their business runs on relationships. New clients come through word of mouth and direct outreach — but as their portfolio grew and agency demand accelerated, manual prospecting couldn't keep up. They needed a pipeline that generated itself.

Ovrhaul's growth depended on finding the right agency partners at exactly the right moment — when they were actively investing in AI, scaling fast, or hiring for the roles that signal a serious AI budget. That intelligence existed in the market, but no one was capturing it systematically.

Manual prospecting meant research, list-building, personalisation, and follow-up — all done by hand, all time-consuming, all inconsistent. Without a system, pipeline velocity was capped by how many hours the team could spend on outreach. That ceiling was too low for the growth they were targeting.

• No signal layer: buying intent existed in the market but wasn't being monitored
• Manual list-building: hours spent researching prospects with no repeatable process
• Inconsistent follow-up: sequences started manually, rarely completed
• No enrichment workflow: contact data assembled by hand per prospect
• Pipeline ceiling: outreach volume capped by team bandwidth, not market size

We built a fully automated signal-based outbound machine that runs continuously in the background — zero SDRs, zero list-building, zero manual research after setup.

The signal layer monitors LinkedIn for two high-intent buying indicators: job postings for AI, Marketing, or Growth roles (a direct signal of budget and intent), and headcount growth above 20% quarter-over-quarter (a signal of an agency scaling fast enough to need AI distribution infrastructure). Both signals map precisely to Ovrhaul's buyer profile.

Every triggered company is automatically enriched — decision-maker name, title, verified email, and LinkedIn URL — without a human touching a record. Enriched leads enter a multi-touch sequence personalised by signal type, company size, and niche. Touchpoints run across email and LinkedIn, staggered over 14 days, with copy tailored to the specific trigger that surfaced each lead.

• Signal 1 — Job Postings: LinkedIn monitoring for AI, Marketing, and Growth roles as active buying signals
• Signal 2 — Growth Indicators: Companies with 20%+ QoQ headcount growth flagged as expansion targets
• Automated Enrichment: Decision-maker contact data appended per company with no manual step
• Multi-Touch Sequences: Email and LinkedIn touchpoints staggered over 14 days, personalised by signal type
• Dynamic Copy: Outreach copy adapts to the specific trigger — job post vs. growth signal vs. industry niche
• Continuous Operation: Signal detected, lead enriched, sequence triggered — fully automated end-to-end

40% reply rate. 20+ booked calls in a single week at peak. Zero manual prospecting from the moment the system went live.

The signal layer was the decisive advantage. Cold outreach that references a company's recent hire or growth trajectory isn't cold — it's timely. Leads respond because the message is relevant to something they're actively dealing with, not because it landed in their inbox on a good day. Timing and relevance did the work that volume alone never could.

The system runs continuously. Every week it surfaces new companies entering the buy window, enriches them, and moves them through the sequence without anyone building a list or writing a follow-up. Pipeline now compounds on its own.