Agentsify AI
WORKED EXAMPLES

The AI brain in production

Not slides. Not mockups. These are actual operational cases: every SaaS we unbundled, every rail we built, every cost we cut. Each one writes outcomes back to an owned database that compounds daily.

CASE 01
Pipeline Sourcing

Outbound Lead Engine

Replaced a $500/month SaaS prospecting platform with a direct API stack at 64% lower blended cost per lead.

The Problem

A traditional SaaS prospecting platform was billing $500/month (~$0.34 blended per mobile lead) to run list queries. Sourcing logic was wrapped behind a UI with credit-expiring limitations and no write-back memory.

The Build

We unbundled the search-and-enrich pipeline. Connected Explee for target geo-sourcing, Exa for search-and-mobile lookup, and Twilio Lookup API for live carrier validation. All records route through Claude Opus for referee checks and true-contact identification. Every validated lead writes to a local SQLite truth table.

UNBUNDLED TECH STACK

Explee APIExa SearchTwilio LookupClaude OpusSQLite

COMPOUNDING MOAT

Every resolved lead and referee outcome writes to a local SQLite cache. Over time this builds a private validated directory that outperforms any rented database.

RAW PERFORMANCE LOGS

Cost Per Leadvs $0.34 before
$0.12
Monthly SaaS Feezero seat lock-in
$0
Lead Validationlive carrier check
Twilio API

Want a system like this?

We map your existing workflows, identify the SaaS seats to retire, and build the owned rails that compound.

ALL CASES AT A GLANCE

Eight systems. One doctrine.

Every case below follows the same four-layer rule: own the brain, rent only the rail, accumulate the outcome data, retire the wrapper.

READY TO BUILD

Map your first rail.

One working session is enough to identify which workflows to collapse first and which SaaS seats to retire. We build the rails; you own the asset.