Not templates. Not merge tags. Research-backed cold emails written for one specific person, using deep research of prospect data.
See It In Action →AI cold email is a fundamentally different approach to outbound. Instead of writing one template and swapping in names, AI researches each prospect individually, then writes a unique email grounded in real data about their business. The hook references something specific, like their ad spend patterns, recent hires, or a gap in their service offering. The result is an email that reads like it came from someone who actually studied their company, because it did.
Reply rates on template-based cold email have dropped below 1 percent for most senders. Prospects have seen every variation of "Hi {first_name}, I saw that {company_name} is doing well in {industry}." That is not personalization. That is a mad lib, and everyone knows it.
You could hire SDRs to research each prospect and write custom emails. But that caps your output at 30 to 50 emails per day per rep, and quality drops when they rush. You end up paying 60K per year for inconsistent output.
Most cold email platforms call it personalization when they insert a first name, company name, and maybe a city. That is not personalization. Real personalization means referencing something only this prospect would recognize, something that makes them stop and think "how did they know that."
We identify who the prospect competes with and how they position against them. This surfaces gaps and vulnerabilities that make the hook hit harder.
Full scrape of the prospect's website. Service pages, case studies, pricing structure, messaging, and positioning. We know what they sell and how they sell it.
Each prospect is scored against your ideal customer profile before any email is written. Bad fits get filtered out. Only high-scoring prospects enter the sequence.
We identify the tools and platforms the prospect uses. This informs the angle and ensures the hook references technology they actually rely on.
Recent press mentions, product launches, funding rounds, and company announcements. Timely hooks that reference real events outperform everything else.
We check if the prospect is running paid ads, on which platforms, and how aggressively. Ad spend patterns reveal priorities and budgets.
The decision-maker's LinkedIn profile surfaces their background, content they post, topics they care about, and connections that create warm angles.
We analyze reviews from Google, G2, Clutch, and industry-specific platforms. Positive reviews confirm strengths. Negative reviews reveal operational gaps.
Geography, description, industry, company size, title, and tech stack data from Apollo. This is the foundation layer that every other enrichment builds on.
Active job listings reveal where the company is investing and where they have gaps. Hiring for sales means they need pipeline. Hiring for ops means they are scaling.
When a prospect replies with interest, the system invites them onto your podcast as a guest. The cold pitch never asks for a meeting. It offers a seat on your show, and that flips the whole dynamic.
You spend 45 minutes in a real conversation with the prospect on camera. By the end they know you, they trust you, and the relationship is warm. The recorded conversation builds the trust a cold email never could, and any fit for working together is a separate, later conversation.
After the episode, the next step is a separate conversation. The prospect arrives already sold on you, so it starts far warmer than a cold booked meeting. That is the Reverse Outbound Engine.
We will walk you through real emails, real research, and real results. 15 minutes, no pitch deck.
Schedule Your Demo →30 recorded conversations with your ideal buyers in 90 days, or it's free, every dollar back if we miss it.