- Specialization
- Computer Vision
- Business
- Software Applications
- Market
- Software Development
- Ecosystem
- Applications
- Customers
- Enterprises
More details
- Organization type
- Commercial Company
- Ecosystem
- Applications
- Business
- Software Applications
- Specialization
- Computer Vision
- Market
- Software Development
- Customers
- Enterprises
- Delivery models
- Hosted Software
- Revenue models
- Usage Based, Subscription
- Listing status
- Not classified
- Latest equity round
- Not classified
- Reported funding amount
- Not classified
About
Human Behavior builds vision-AI product analytics that watches user web sessions and extracts behavior patterns driving retention and revenue without manual event tracking. It sells to product teams at high-growth startups, differentiating itself by analyzing session replays contextually rather than requiring teams to rely on aggregate analytics or manually watch videos.
Market
Human Behavior competes in AI-native product analytics and digital experience or behavioral analytics, serving teams that want to understand how users actually interact with their products. Its differentiation is that vision models automatically watch user web sessions and extract behavior patterns, friction, bugs, and retention or revenue drivers, reducing the need for manual replay review. It also extends beyond observation by continuously recommending targeted, page-level UI/UX improvements, while competitors primarily offer adjacent combinations of product analytics, session replay, and digital experience analytics.
Human Behavior targets fast-moving, high-growth startups, especially Series A and B companies with web products. Its primary buyer is the product team, which uses the platform to understand feature usage, identify bugs and friction, and improve retention and revenue.
At a Glance
Problem
Human Behavior addresses the product-visibility gap faced by fast-growing startups. Conventional analytics depends on manually tagged events, clickstream data, and people watching session replays, making it difficult and expensive for product teams to understand how customers actually use a product. The immediate economic pain is staff time: customer feedback indicates that Human Behavior can save hundreds of hours spent reviewing replays and identifying pain points.
Its central use case is turning every user session into a continuous stream of actionable product intelligence. Instead of discovering feature problems, bugs, or churn only through anecdotes or delayed analysis, teams receive regular signals about which features are being used, where users get stuck, which bugs appear, and which customers leave.
Product / Service
Human Behavior is an AI-native product analytics platform that watches user sessions and converts them into insights for product teams. It auto-instruments event listeners across an entire product without code changes, indexes pages, components, and user flows into a living product map, and analyzes session recordings to capture how users interact with the product. It also uses autonomous browser agents to navigate and validate live user flows, while connecting to databases, CRMs, error tracking, and existing analytics tools.
The delivery model is largely automated: setup is advertised as taking about 90 seconds, after which the system surfaces findings in the team's inbox and can provide context for code agents to fix bugs. The benefit is a shift from manually inspecting isolated replays to giving product, engineering, and growth teams a continuously updated understanding of user behavior, including the context behind friction rather than just numerical events.
Market
Human Behavior competes in AI-native product analytics, at the intersection of session replay, product analytics, and developer tools analytics. Its differentiation is replacing event-based instrumentation and manual replay review with vision-model analysis of all sessions and autonomous testing. The available materials do not identify named direct competitors, so the clearest comparison set is the established session-replay and event-based product-analytics market rather than a specific rival.
The company has meaningful early traction rather than appearing purely pre-launch: it was founded in 2025, is an active Spring 2025 Y Combinator company, has raised a reported $5 million seed round from investors including Y Combinator, General Catalyst, and Vercel, and says it serves hundreds of companies. TechCrunch reported that its customers were mainly fast-moving Series A and B startups receiving daily summaries, while customer testimonials describe substantial time savings and product decisions influenced by the system. A reliable current revenue figure is not disclosed in the available evidence, so revenue status cannot be determined from the research.
Founders & Leadership
Funding History
General Catalyst, Y Combinator, Vercel
Recent News
Human Behavior launched on Product Hunt with a product that captures events, errors, and session replays, uses AI to identify behavioral issues, and turns those findings into actions. The company positions the product as an alternative to dashboards that only report what happened.
Human Behavior publicly reported a $5 million funding round to build its AI-native product analytics platform. The reported investors include Y Combinator, General Catalyst, and Vercel.
Y Combinator listed Human Behavior’s company launch and positioned the product around revealing why users stay, leave, or pay.
TechCrunch reported that Human Behavior, a four-month-old YC startup, raised a $5 million seed round. The company uses vision AI to analyze online user behavior and sessions.
Active Roles
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Get notified when they postBusiness Model
Human Behavior uses a usage-based pricing model: $500 per month includes 8,500 sessions, with additional sessions priced at $0.06 each. It sells this product analytics platform directly to product teams at startups.