Overview

Varos, a leading competitive intelligence firm, partnered with StackAI to automate its previously manual company categorization workflow, cutting more than 800 hours of labor and improving lead qualification accuracy and scale. By building a custom AI agent tailored to its research workflow, Varos streamlined web scraping, product data extraction, and classification using LLMs, all without expanding its technical team.

• 800+ hours saved by eliminating repetitive manual research
  
  

• 1-week deployment of a fully operational AI agent without added engineering resources
  
  

• Faster, more consistent lead qualification, improving downstream sales and marketing efficiency

The Problem: Manual Lead Qualification Slowed Growth

Varos knew it needed a more scalable way to qualify leads. Its operations team was responsible for scanning online company profiles, analyzing product offerings, and assigning categories to incoming leads. This process, done manually, required hours of repetitive research and made it difficult to ensure consistent classification at scale.

Manual research also limited the volume of companies that could be evaluated and created delays in delivering insights to marketing and sales teams. With growing data inputs and mounting pressure to accelerate operations, Varos needed a way to automate this process quickly, but without sacrificing precision.

The Solution: AI-Powered Categorization With StackAI

Using StackAI’s no-code builder, Varos built a web research AI agent that automated every step of lead qualification. The agent scraped public company data, extracted product details, and applied consistent classification logic using LLMs.

Team members simply uploaded lists of companies and received structured, categorized outputs at scale. Better yet, the setup was live in just one week, and the ability to customize prompts meant the classification logic could evolve alongside business needs.

This AI agent has saved over 800 hours of employee time.