About Screw Analysis
We're on a mission to make screw compressor analysis accessible, accurate, and actionable.
Our Story
Screw Analysis was founded in 2022 by a team of engineers with decades of experience in industrial compressor systems. We recognized that while screw compressors are critical to many industries, the tools for analyzing their performance were often complex, expensive, and inaccessible.
Our team set out to create a solution that would democratize compressor analysis, making it available to maintenance teams, engineers, and operators of all skill levels. By combining advanced analytics with an intuitive interface, we've created a platform that transforms complex data into clear, actionable insights.
Today, Screw Analysis serves customers across manufacturing, oil and gas, food processing, and many other industries where reliable compressed air systems are essential to operations.
Our Values
Reliability
We're committed to providing accurate, dependable analysis you can trust to make critical decisions.
Accessibility
We believe powerful analysis tools should be accessible to teams of all sizes and technical backgrounds.
Innovation
We continuously improve our algorithms and features to provide cutting-edge analysis capabilities.
Why Choose Screw Analysis?
Specialized Expertise
Our platform is built specifically for screw compressors, with algorithms tailored to their unique characteristics.
Time Savings
Reduce analysis time from hours to minutes with our automated processing and intuitive interface.
Actionable Insights
Get clear recommendations, not just data, to help you make informed maintenance and optimization decisions.
Cost Effective
Avoid expensive consultants and specialized software with our affordable subscription-based platform.
Our Team
John Smith
CEO & Co-Founder
20+ years experience in industrial compressor systems
Sarah Johnson
CTO & Co-Founder
PhD in Mechanical Engineering, specializing in fluid dynamics
Michael Chen
Lead Data Scientist
Expert in machine learning and predictive maintenance algorithms