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How brands sell when buying becomes asking

Shoppers ask questions on your site, ask ChatGPT what to buy, and send AI assistants to shop on their behalf. Every store on earth was built for clicking. We build for the ask.

One intelligence per brand, trained on its catalog, policies, and every conversation, running six revenue jobs. The platform sells to the humans on the site today and represents the brand to the AI assistants buying tomorrow.

Backed by

Backed by Y Combinator

Building the selling side of the AI era.

Buying is getting an upgrade: people ask ChatGPT what to buy, send AI assistants to compare, and expect stores to answer like people. Selling hasn't kept up — in a $5T industry, that's the gap. Kinect is an engineering team pointed at it, building the intelligence that lets a brand meet the ask everywhere it happens and stay unmistakably itself while it does.

Why Kinect

When buying becomes asking, the best answer wins.

Kratik and Varun met at Reevo, building AI that read B2B sales calls: which objections killed deals, which signals meant a buyer was ready, why one rep closed and another didn't. Kratik ran Conversational Intelligence; Varun built the context graphs underneath it.

The same hole was sitting in ecommerce, unfixed. Brands track every click, every add-to-cart, every checkout, and capture almost nothing about what the shopper actually wanted. The search bar takes a query and throws the intent in the trash. The shopper with one unanswered question doesn't open a ticket. They leave, and the brand never learns why.

So we built the thing that answers. An AI sales rep grounded in the brand's own catalog and policies, that handles the question in the moment and sells the way the brand's sharpest employee would: in the brand's voice, never a generic bot. Every conversation it has becomes first-party intent data the brand has never had. And the same catalog we teach it becomes the one AI assistants can read from the outside.

Today that one intelligence runs six revenue jobs for every brand on Kinect — the platform.

Our values

Own your area

Kinect runs on ownership. Every part of the company has one clear owner with the context and the room to run, and the outcome carries their name. People here would rather be trusted than managed.

Lean by design

We hire selectively and stay small on purpose: high-impact, high-velocity people in seats that matter, with AI doing the rest. We run our own company the way we tell brands to run their stores.

Founder at work
Shoppers at a market
Team dinner
Evening event

Everyone is a shopper

We all buy things online, so everyone here has product instincts. Ideas and feedback get weighed on merit, not title. And customer first is literal: the job, every day, is making our customers' lives better.

Shape the frontier

We spend our time on where buying is going, not where it's been. The point is to set the industry's direction and be early to what's next, not chase trends once they're safe.

Our Team

A team that's shipped AI, data, and commerce systems at the frontier

Google
Meta
Anduril
Verkada
Sephora
MongoDB
Ironclad
Reevo
UCLA
UC Berkeley

Founders

Kinect was founded in San Francisco by Kratik Agrawal and Varun Kandula, and is backed by Y Combinator. The team has trained models at Anduril, scaled data systems at Google and MongoDB, shipped AI with Sephora, and built conversational intelligence at Reevo. It ships every week, puts stores live the same day, and every brand works directly with the founders. And it's growing.

Kratik Agrawal

Kratik Agrawal

Co-founder & CEO

Started on Google's ads team, going deep on how segmentation and matching work at scale. From there he trained ML models at Anduril and launched new enterprise lines at Verkada, then led Conversational Intelligence at Reevo, an $80M Series A backed by Khosla and Kleiner Perkins, building the systems that helped B2B sellers walk into every meeting better prepared. San Jose native, UCLA CS.

Varun Kandula

Varun Kandula

Co-founder & CTO

Data and infrastructure to the core. He worked on the data context team at MongoDB and built context graphs at Reevo, and consulted for Sephora on their AI features in 2023. During COVID he ran his own e-commerce store at $10K a month, so he knows firsthand what it takes to run ads and fight for conversions. D1 squash player. UC Berkeley.

The fastest way to know us is a demo

We'll run the rep against your own catalog: your products, your policies, your hardest customer questions. And if you'd rather build this than buy it, we're hiring.