Hey everyone,

We’re Moe and Theo, and we’re building Webhound.

TL;DR

Webhound is an AI research agent that builds custom datasets from web research. Instead of spending weeks manually gathering data, simply describe what you need and Webhound automatically finds, extracts, and organizes it into structured datasets you can export.

Some examples are:

• “Find 100 AI/ML YouTubers with 50K-100K subscribers, their email addresses, and latest video view counts.”
• “Track pricing, features, and customer reviews from both Reddit and Youtube for 30 CRM competitors including Salesforce, HubSpot, and Pipedrive.”
• “Collect 500 vacation rental listings in Bali with photos, pricing, amenities, and guest reviews from multiple platforms to analyze market trends.”
• “Identify 200 early-stage e-commerce startups on Shopify or WooCommerce, along with founder names, contact emails, and product categories to build a lead list.”

https://www.youtube.com/watch?v=cG1SiKznpHs&pp=0gcJCcEJAYcqIYzv

❌ The Problem

Data collection is painfully manual and slow. Need to research 100 competitors? That means visiting 100 different websites, copying information into spreadsheets, and repeating this process for every data point.

This creates two major problems:

• High effort: Hours of tedious manual work, clicking through sites, and organizing data
• Slow speed: What should be quick research turns into weeks of work

👷 Our Solution

Webhound makes data collection effortless and fast.

Effortless: Simply describe what you need in plain English. Webhound handles everything in the background while you focus on other work.

Fast: A fleet of parallel search agents collect data simultaneously across multiple sources, turning weeks of manual work into hours.

Export clean, structured datasets as CSV, Excel, or JSON.

🙏 Our Ask

Want to try Webhound? Access is currently limited to 5 datasets per week and one at a time, but if you're interested in higher limits to automate your research workflow, please reach out to us at team@webhound.ai.

👬 The Team

Moe and Theo have been friends for 6 years and were roommates in college (in the room where Evan Spiegel founded Snapchat).

Since graduating, Moe’s built a bunch of AI search tools, including Instaclass (turn any topic into a full search-backed course) and Remy (think Perplexity, but for video).

Theo went deep on data, building and scaling Quicklime, where he helped film studios and streaming services collect the info they needed to make smart bets.