At TekRevol, we’ve always believed in building things we’d use ourselves. Reverto is exactly that.<\/p>\n
Every agency of a certain size carries the same quiet problem: a CRM full of contacts that represent years of relationship-building, outbound effort, and marketing spend, and a follow-up process that falls apart after the second touch. For the first several years of our growth, we were no different. By 2023, TekRevol had accumulated over 130,000 contacts in HubSpot. New inbound traffic had slowed. The pipeline, once fed by a steady stream of referrals and outbound, needed a different kind of fuel.<\/p>\n
The answer wasn’t hiring more SDRs or running more paid campaigns. The answer was in the database we’d already built.<\/p>\n
Our BD team is good at relationships. They’re not designed to send the seventh follow-up to a contact who went cold eight months ago, on a Tuesday at 10am, referencing the last conversation thread, across email, SMS, and LinkedIn simultaneously. No human team does that consistently. Most stop at touch two.<\/p>\n
That gap between “touched” and “converted” is where revenue disappears, not just for TekRevol, but for every services business that generates demand without the systems to capture it.<\/p>\n
We knew this. We’d seen it across clients. So we built Reverto to solve it, first for ourselves, then for the market.<\/p>\n
Reverto is now TekRevol’s founding tenant, running the agency’s own dormant pipeline as the first live proof point of the platform. Here’s what that actually looks like day-to-day:<\/p>\n
The system ingests our existing contact list, segmented by last interaction date, project type, industry, deal stage, and conversation history. It then runs each contact through an Engagement State Machine (ESM) that decides, in real time, which channel to use, what message to send, and when to hand off to a human closer.<\/p>\n
Unlike static drip sequences that send the same email to everyone on day one, day three, and day seven, Reverto’s ESM carries a shared state across all four channels, email, SMS, voice, and WhatsApp. If a contact opened an email but didn’t reply, the next touch isn’t another email. It’s a different channel, with a message that acknowledges the prior touch. If a contact responds to a voice outreach, the email thread is updated. Every agent in the sequence knows what every other agent did.<\/p>\n
The decision layer surfaces a confidence score with every AI-generated draft, so our BD team isn’t flying blind. They see what Reverto proposes to send, why, and they can override it before it goes out. “AI drafts, humans decide” is the posture. It’s the only posture enterprise-facing BD can operate under.<\/p>\n
The reactivation rates from dormant contacts are meaningfully higher than cold outbound, often 3\u20134x the reply rates. People who already know TekRevol respond differently than cold prospects. They need a relevant reason to re-engage, delivered at the right moment, through the channel they actually use. Reverto does that systematically.<\/p>\n
The second learning is operational: the value isn’t in any single campaign. It’s in the compounding. A dormant contact touched in month one who doesn’t convert might surface again in month four after a trigger event in their business, a new funding round, a new hire, a product launch. Reverto keeps them in the sequence. Human BD teams move on.<\/p>\n
TekRevol’s BD challenge isn’t unique. It’s the same challenge running through every service agency, every SaaS company with a trial database, every healthcare operator with unconverted intake inquiries, every auto dealership with 8,000 sold customers sitting in a DMS. The database is the asset. The problem is the follow-through.<\/span><\/p>\n We built Reverto to solve it for ourselves first because we believe the best products come from operators who’ve lived with the problem. We’re not selling a concept. We’re running it. And now we’re making it available to the verticals where the pain is highest and the ROI is most measurable.<\/span><\/p>\n If your business is sitting on a pipeline it paid to build but never fully worked, that’s the conversation we want to have.<\/span><\/p>\n