Young Innovators Raise $5M from YC and General Catalyst to Investigate Online Behavior Using Vision AI
Amogh Chaturvedi is running on little sleep but plenty of conviction at 6 a.m. He’s groggy, apologetic for rescheduling, and still reeling from a recent scare involving a family member and an electric scooter.
Yet within minutes, the 20-year-old Stanford dropout snaps into focus, guiding me through how he and his co-founders sold one startup at 19, landed in Y Combinator, and raised $5 million for their next venture, Human Behavior.
Launched just a few months ago, Human Behavior is betting that vision AI can achieve what analytics tools like Mixpanel and PostHog have struggled with: providing companies with a genuine understanding of how users engage with their products, including the reasons behind conversion or churn.
Rather than depending on manually tagged events or clickstream data, Human Behavior claims its AI observes actual user session replays and generates insights, addressing product teams’ most pressing inquiries without consuming hours of coding effort.
The 4-month-old YC startup wrapped up its $5 million seed round in just two days (a trend that’s becoming common for current YC companies), with support from backers like General Catalyst, Paul Graham, Vercel Ventures, and Y Combinator.
“We could’ve engaged in financial engineering because we received more offers with higher valuations, but we didn’t want that,” stated the CEO.
L-R: Amogh Chaturvedi (CEO), Chirag Kawediya (COO), Skyler Ji (CTO)
Image Credits: Human Behavior
Chaturvedi met his co-founders, Skyler Ji and Chirag Kawediya, both 22, at a hacker house he organized in 2023, using it as an opportunity to live and build with friends after his freshman year at Stanford.
Their first startup, Dough, was an e-commerce accounting tool they bootstrapped. Like Chaturvedi, Ji left college (departing from Berkeley), while Kawediya chose to graduate.
Although YC was initially doubtful about Dough’s market potential, the team was accepted into the accelerator’s spring batch this year with the expectation they would ultimately pivot, according to Chaturvedi. They did just that soon after by consulting every customer and asking about any other challenges they faced.
The feedback was clear: While Dough could indicate which products were selling or not, customers wanted to know why. Addressing that required analytics driven by behavioral data, rather than just accounting reports.
With this new direction, the team sold Dough for six figures to Employer.com, the very company that acquired Bench, and committed fully to Human Behavior.
Kawediya explains that companies using conventional analytics often need engineers to establish event trackers for every button and click, consuming hours or even weeks of development time.
For a dynamic startup, that’s far from optimal. “Even once you have that data, you’re still faced with the larger question of how users truly interact with your product to enhance it,” he adds.
Session replays aren’t a new concept, but until recently, computer vision models haven’t been precise enough to analyze them at scale. Now they are, and Human Behavior employs this technology to summarize and segment thousands of hours of footage. “Why spend countless hours writing code to track clicks when we can simply view the video?” Ji adds.
Currently, Human Behavior’s clientele — primarily fast-growing Series A and B startups — receive daily summary emails showcasing which features were in use, which bugs emerged, and which users churned.
The founders refer to session replays as an “untapped goldmine.” At present, Human Behavior assists teams in understanding users and resolving bugs. Over time, the same dataset could enable automated QA and integrated IT support. Their vision is to transform Human Behavior into the Datadog of session replay, creating numerous products from the same core data.
Building with cutting-edge technology from the ground up is how the founders plan to compete with established players like Mixpanel and PostHog. “For some of these companies, replicating what we have could be challenging because their architecture may not support the transition without starting from scratch,” remarked Chaturvedi.
