Source: https://goodleads.club/how-we-build.html Formation-Grade Lead Intelligence · AI-Native # From Just Leads To _Good_ Leads. Old players scraped it last quarter. We built yours this morning. **The difference isn't the list. It's the engine behind it — and when it runs.** [Buy GoodLeads](https://app.goodleads.club/buy.html) [See how it works →](https://goodleads.club/#how) Data built at _Day 0_ Triggered at state filing. Before anyone else knows the business exists. Sources per record _11_ joined State filings, property records, identity verification, email validation, skip trace, and more. Agent sessions today _24/7_ Morning standups. Evening sweeps. Auto-improving while you sleep. The Problem with Old Players ## Everyone Has The Same List. Apollo · ZoomInfo · Legacy Databases ### The Old Way * Data scraped and batched quarterly — sometimes annually * By the time you get it, 200 other reps already have it too * Phone numbers validated by existence, not deliverability * Contact titles guessed from LinkedIn, not decision-maker logic * No signal on when the business formed — or if it's even active * You compete on the same names, same emails, same timing * Static database. Quality degrades with every passing month. GoodLeads.Club · Agent-Built ### The GoodLeads Engine * Record built within days of state filing — before it's anywhere else * Nobody else has it. You own first contact. * 7-signal Reachability Score: phone validity, inbox activity, identity match, and more * Contact Relevance Score separates decision-makers from paperwork processors * Formation date, filing type, registered agent — full context baked in * AI agents improving every join, every field, every week * Living data engine. Gets better over time. How We Build ## Not a Database. _An Agent Org._ GoodLeads runs the same way a software company ships product — through an organization of specialized agents: managers, peers, escalation paths, and a culture documented in a wiki. **Not one AI. A team. Working today.** Triggered at Formation The moment a state records a new business filing, our pipeline runs. **Day 0 data.** Not day 90. Platform EM + State GMs A Platform Engineering Manager agent coordinates State GM agents — each owning a territory, running **morning and evening standups.** Cross-Model Code Review Every pipeline change reviewed by **Claude and Codex** — different model families — eliminating same-family blind spots before anything ships. Agent Organization · Live in Production Platform EM — Horizontal Scope Reviews every PR · Daily org sweep · Friday recap · Auto-fixes mechanical gaps · Cross-model code review with Codex State GM CO State GM FL State GM VA 7 sessions · all exit 0 · 0 engineer interventions today Self-Improving Data ## Every Field Gets Better Every Week. The data you get today is better than what we shipped last week. Next week's will be better still. Three self-improving loops run continuously. 01 Comment Corpus → ML Signal Founder commentary on record quality gets clustered, scored, and converted into **formal eval criteria.** Manager intuition becomes machine learning training signal. Competitors try to replace this with feedback forms. It doesn't work. 02 Forward-Replay Experiments Variants run through the **same production context-builder** as live agents — not a separate one. Experiments actually predict production. Most teams compromise this. Once compromised, experiments stop meaning anything. 03 Auto-Revert & Verify Agents don't just ship. They **ship, verify, and auto-revert** if something regresses. Per-vendor verifier registry runs daily. The pipeline doesn't drift. The data doesn't silently get worse. Two Scores. One Record. No Guessing. ## We Don't Just Check _If_ It Exists. Every record ships with two proprietary scores, each trained on signals old databases don't collect. A phone number that exists and a phone number that **answers** are not the same thing. Score 01 Reachability Score 0 – 100 · 7 signals * Phone validity Signal * Email deliverability Signal * Inbox activity Signal * Identity match Signal * Phone type (mobile vs. VOIP) Signal * Address precision Signal * Location confirmation Signal Score 02 Contact Relevance Score 0 – 100 · Decision-maker logic * Owner vs. registered agent distinction Signal * Filing role vs. operational role Signal * Single-member vs. multi-member entity Signal * Title inference from filing type Signal * Cross-source identity confirmation Signal Separates the decision-maker from the paperwork processor. Old databases guess from LinkedIn job titles. We infer from the filing itself. Defensibility ## What's Hard to Copy. And Why. A competitor can copy the surface in a sprint. **Copying the architectural choices behind it takes a year** — each one presupposes decisions made months earlier. | Component | Why It's Hard to Replicate | Difficulty | | --- | --- | --- | | Comment corpus → judge scorer | Requires a manager who comments in writing on a stable surface, a clustering pipeline, and the trust-ladder gate. Feedback forms don't substitute. | High | | Forward-replay experiment harness | Variants share the production context-builder — not a separate one. Most teams compromise this; once compromised, experiments stop predicting production. | High | | Trust ladder + tier-keyed autonomy | Policy file is small, but routing Tier-S changes to plain-English review — not Slack DMs to engineers — is a cultural commitment most teams won't make. | Med–High | | Cross-model code review | Two API integrations and an aggregator. Defensible because Claude and Codex catch different classes of errors — same-family review misses this. | Med | | Day-0 formation trigger | Requires state-level filing integrations built and maintained per-state. Each state uses a different schema and cadence. There are no shortcuts. | High | Formation-Grade Lead Intelligence ## Own _First Contact._ The business just formed. Nobody's called them. Nobody's in their inbox. That window doesn't stay open. [Buy GoodLeads](https://app.goodleads.club/buy.html) Formation-grade · AI-built · Self-improving · Yours before anyone else's --- Agent resources: https://goodleads.club/llms.txt Operational guide: https://app.goodleads.club/llms.txt Live counts and prices must be fetched from the API; examples and historical metrics are not live quotes.