Competiflow: Automating Competitor Intelligence

Parsing pricing pages is a nightmare because formats are completely unpredictable. I tried building my own automation using cron jobs and custom parsers for blogs and changelogs, but the moment I tried to track pricing, everything broke. Standard scrapers can't handle the layout variance, and sending raw HTML to an LLM proved to be both expensive and unreliable due to non-deterministic outputs—basically "garbage in, garbage out."

I initially tried Visualping, but it only solves the detection problem, not the analysis problem. I was still spending way too much time manually reviewing pixel changes and filtering out noise like cookie banners or CSS updates.

To solve this, I spent a month developing Competiflow. The goal was to move from "pixel diffing" to "data diffing." Instead of alerting me that a page changed visually, the system identifies specific URLs (pricing, docs, blog, changelog), extracts structured fields like plan names and prices, and compares the actual values.

For the blog monitoring side, I integrated a workflow that generates keywords and checks search volume, which helps in separating actual signal from marketing noise.

Technical highlights for those interested in the AI workflow:

• Data Extraction: It extracts specific fields rather than raw text to avoid noise.
• Integration: It includes a REST API and an MCP server. I've been using the MCP server within Cursor to keep an eye on competitors while I'm coding.
• Analysis: Provides a concise summary of changes with before/after text and the source URL.

The tool is available at https://competiflow.com if anyone wants to test the extraction logic on their own competitor list.