I spent 2.5 years building a marketing engine nobody can see without installing it. So I built a free distortion calculator.
I've been building CDAI solo since early 2024. No co-founder. No funding. No team.
The engine requires a HubSpot install before anyone sees value. Nobody installs something they've never seen work. That's the distribution wall I've been hitting.
So I built a free calculator as the entry point.
You enter your ad spend, leads, revenue, and whatever costs apply to your business — vendor fees, compliance costs, chargebacks, refunds. It shows you what your dashboard reports versus what your campaign actually cost per lead. Takes two minutes. No install. No pitch.
Every signup also joins The Margin Gap — a newsletter I'm building around the gap between what ad platforms report and what campaigns actually cost. Zero real subscribers today.
If you're in insurance, mortgage, solar, legal, home services, Medicare, or clinical trials and you're running paid ads — this is for you.
If you've cracked cold distribution for a product that requires an integration before it shows any value I'd genuinely love to know how.
https://alloceraintelligence.com/
The calculator works if it exposes a surprising gap that naturally creates the next question. I'd track which cost layer changes the decision most, then make the signup promise specific: 'we'll benchmark this gap for your vertical,' not a generic newsletter. Zero subscribers means the bridge from result to ongoing value is unproven; it doesn't yet say the calculator itself is weak.
The interesting shift isn't replacing SaaS with AI agents—it's replacing software navigation with business intent. I'd keep validating whether SMBs are buying autonomous agents or confidence that their operations keep moving forward without them becoming the integration layer between dozens of tools.
Exactly right — and worth clarifying since "AI agents" is getting thrown around a lot: CDAI isn't an agent. It's ~17,000 lines of deterministic math. No model, no autonomous decisions. Same inputs always produce the same directive. Fully auditable.
The integration layer point is precisely what it solves. Here's what that actually looks like in code:
Ad platforms connected: Meta, Google, LinkedIn, Bing
CRMs connected: HubSpot, Salesforce, GoHighLevel
Lead networks: Boberdoo, Ringba, CallRail
Billing: Stripe
Every nightly sync, the engine pulls spend from the ad platforms, revenue from the CRM, and reconciles them against 7 cost layers the ad platforms never see — broker fees, compliance costs, chargebacks, refunds, platform fees, partner payouts, variable costs. Then it issues one of 8 directives per campaign: SCALE, HOLD, CUT, PAUSE, QUARANTINE, RENEGOTIATE, INVESTIGATE, or FLAG.
The SMB never touches any of it. Meta and HubSpot don't talk to each other. CDAI is the only place that sentence exists: you spent $2,265, generated $74 in revenue on that campaign, that's -344% margin, stop spending.
It also goes deeper by vertical. Clinical trials run 150-day sales cycles. Insurance runs 21 days. Senior care runs 90. A campaign that looks dead at 30 days may be your best campaign at 90. The directive formula adjusts per vertical because the same math at the wrong window gives you the wrong answer.
The confidence question is what I'm actually validating — whether an SMB will act on a directive they didn't generate, even when every number is transparent and auditable. That's the real adoption question.
That's exactly the part I found most interesting.
Reading your reply gave me one thought about what changes once founders trust the reasoning behind a directive but still have to trust themselves enough to act on it. I don't think I could do that idea justice in a thread because it really depends on how you're positioning CDAI.
If you're interested, what's the best email to reach you on?