I direct AI to build software. My job is knowing when it’s wrong.
I’m Nisarg Gurjar. I’m a founder and operator. My team is AI; my job is judgment — what to build, what’s correct, what ships. The result: live SaaS, automation carrying real revenue for a real events company, an iOS app, a desktop app. Everything in this story is real, tested, and in use.
Ajna. A sales call becomes an approved quote, for any event vendor.
Multi-tenant SaaS: call transcript in → reviewed, human-approved, branded quote email out.
Quote Automation. Real revenue, through a pipeline the AI can’t misuse.
A sales call becomes a branded email, calendar invite, CRM log, and Slack update — after a human taps Approve.
Workflow Tracker. Hundreds of event tasks, zero silently dropped.
Task tracking for an events company — a workflow engine with prerequisites and triggers, plus a Slack bot that escalates overdue work.
I decide what should exist. AI writes the code. A system of gates decides what ships.
12 custom skills + 6 guardrail hooks — including guardrails against my own AI touching secrets or sending real email.
LLM features pass adversarial, must-be-100% eval suites before going live. Twice, they caught what tests couldn’t.
Nothing is done until the real user flow works end to end — logs checked, database verified, success seen.
Run an events business? I built Ajna for you.
AI automation for wedding & event vendors — quotes in minutes instead of days, a human always in the loop.