Deepak Kaushish Sharma Email  /  LinkedIn  / 

Builder &
AI Founder

I build AI products end-to-end from psychology-first principles — real behavioral intelligence systems, not wrappers. 15 years across product, engineering and growth at OYO, Foodpanda, Delivery Hero, Zepto, Dell, and Citi, where I now work on agentic AI in payments.

Python / React / Next.js
Node.js / AWS / MongoDB
LLMs / Agentic RAG
Behavioral AI

Products I've Built

4 shipped, 4 live
Kritheon01

Behavioral intelligence that replaces market research with prediction.

Describe your product, campaign, or strategy and get a complete prediction report: how your audience will respond, what drives their decisions, and where they'll push back.

Independent behavioral profiles report purchase intent, emotional response, and reasoning — with statistical validation, confidence intervals, and segment breakdowns. Minutes, not 6–8 agency weeks. Validated across India, US, Canada, UAE, and UK.

Python · LLMs · MongoDB · Vercelkritheon.com ↗
CinePredict02

A virtual test screening for your script.

Upload a screenplay, get a complete greenlight package: audience intelligence, box office modeling, marketing direction, and talent impact analysis in one report.

The financial engine runs 10,000 Monte Carlo simulations with break-even and ROI at multiple budget levels — plus trailer hooks, taglines, viral moments, and risk flags. Native to both Hollywood and Indian cinema.

React · Python · LLMs · Three.jscinepredict.com ↗
InstaRecs03

A recommendation engine that makes everyday decisions effortless.

Tell it what you're deciding and get a personalized recommendation backed by reasoning — food, gifts, fashion, entertainment, travel — tailored to your context and constraints.

The engine learns your taste profile across categories and sharpens over time. Specific picks with explanations, not generic top-10 lists — handling budget, dietary needs, occasion, and mood.

Python · LLMs · Flask · MongoDB · AWSinstarecs.com ↗
Kidsightful04

Child development intelligence that gives parents real clarity.

A structured, age-specific assessment produces a personalized developmental profile: cognitive patterns, emotional tendencies, social dynamics, and learning style.

The engine analyzes responses against developmental benchmarks for ages 2–18 — insights a child psychologist would take multiple sessions to surface, from toddler milestones to adolescent patterns.

Next.js · LLMs · Clerkkidsightful.com ↗

How I Build

Method
01Full-stackPython backends, React/Next.js frontends, cloud-native on AWS.
02Real AI architectureLLMs, behavioral modeling, predictive systems. Not wrappers.
03ShippedAll four products are built, deployed, and running in production.
04SoloDesigned, built, and deployed end-to-end. No team, no outsourcing.

Career

15+ years
CitiVP TechnologyDriving Digital Wallets & Agentic Commerce. Built an internal Gen-AI tool on Agentic RAG that auto-writes feature docs and saves hundreds of analyst hours.
ZeptoHead of CatalogUsed LLMs and Gen-AI to re-classify the catalog and fix data quality at India's fastest-growing quick commerce company.
OYODirector, Content OpsScaled content operations at India's largest hospitality company.
Delivery Hero / FoodpandaGlobal Head, Content & Product OpsRan online store, catalog and content operations across global markets, with deep product management of the platform.
EarlierProduct & EngineeringAcross consumer tech, fintech, and AI — including Dell.

Let's build
something real.

deepak.kaushishs@gmail.com LinkedIn ↗