Work
GTM systems and
AI products I've built.
Engineering background applied to revenue problems. The projects below are real systems — built, shipped, or actively in production.
Projects
GTMe AI
SaaS ProductIn developmentAI-native outbound sales automation. Finds leads, writes personalized outreach, reads replies, and decides the next best action per lead — with a confidence-policy-based approval queue so humans stay in control of the decisions that matter.
GTM Pipeline Tool
Internal ToolBuiltAI-powered outbound pipeline with two modes: prospect a target company (research → leads → personalized emails), or surface hiring managers at companies actively recruiting GTM Engineers and generate personalized outreach to them. Claude Sonnet handles the research and email generation layer.
GTM infrastructure built end-to-end — CRM architecture, enrichment pipelines, AI-powered outbound, attribution systems. The gap between a GTM playbook and actual pipeline is an engineering problem. This is what solves it.
GTM Engineering Handbook
Open ResourceGrowingThe field notes, playbooks, and deep dives from neerajsujan.com — organized by topic. Clay workflows, enrichment recipes, outbound system designs, AI agent architectures. Open and searchable.
Training
Revenue Cartel — Operator Deployment
Sept 2026 – Nov 2026
Live 8-week operator program building six production-grade GTM machines on real accounts: Intent Signal Engine (Clay, RB2B, Apollo), AI Research Agent (Claude, Claygent), Deliverability System (Smartlead), Hyper-Personalized Outbound sequences, Pipeline Automation Loop (n8n + CRM sync), and a full integrated capstone.
GTME.SCHOOL
Sept 2026
Intensive GTM engineering program covering ICP definition, TAM/SAM/SOM mapping, buying signals and intent triggers, offer and message-market fit, and GTM strategy execution.
Stack
Enrichment & Data
Intent & Signals
Outbound & Automation
AI & Engineering