Leadership
Built by pricing practitioners, not outsiders looking in
HXG1 was built by people who have spent their careers doing the work the platform is designed to support.
When we say we worked in pricing, we mean pricing was the day-to-day job. We have spent years reverse-engineering historical pricing from protests and FOIA documents, turning messy downloads from FPDS and other sources into usable competitive intelligence, developing and defending PTWs, building Excel pricing models, finding ways to take cost out without breaking the technical story, puzzling through clunky government templates, pushing back on late-in-the-game decisions to add bodies or software to the solution, sweating over late subcontractor and vendor quotes, responding to last-minute executive changes, cancelling weekend plans for 48-hour BAFOs, decoding year-old files for kickoff teams after a win, and, yes, going back through losses to figure out what we missed.
We know what goes into a real pricing decision because we have made those decisions ourselves, under the same deadlines, uncertainty, and competitive pressure as the teams we support today.
HXG1 is the result of taking that practitioner experience and asking what becomes possible when you combine it with modern data science and machine learning.
Joe Readyhough
Co-Founder
Joe has been pricing federal captures long enough that he priced Y2K proposals, and he was a heavy user of both INPUT and FedSources. Since then he has led price-to-win on strategic captures, stood up enterprise PTW teams, and run M&A for a major systems integrator. He served as CEO of a government contractor that grew rapidly and was successfully sold. Joe also led an AI and data science company building software for the U.S. Intelligence Community. At HXG1, he brings together deep pricing expertise, executive perspective, and experience turning advanced analytics into business applications.
Michael Goodrich
Co-Founder
Michael is a data scientist and pricing strategist who has worked on everything from small task orders on the original T4 vehicle to multibillion-dollar single-award procurements. Throughout his career he has combined hands-on pricing strategy with advanced mathematical optimization, simulation, and data science to quantify pricing tradeoffs. He has also built data science tools for Corporate Growth at a major systems integrator, turning large, messy public datasets into usable signals for price-to-win and competitive intelligence. At HXG1, he brings this experience together to build scalable analytical models for competitive federal bids.
About HXG1
Why we built HXG1
Traditional price-to-win and pricing strategy depend heavily on experienced people assembling market data, finding comparable contracts, interpreting RFP features, assessing competitors, and applying judgment to determine where a winning price is likely to land.
We did that work for years.
We also saw its limitations. The analysis is time-intensive, difficult to standardize, and inherently constrained by how much information a person can find and evaluate. The deepest analysis therefore tends to be reserved for a company's largest pursuits, even though the same decisions have to be made across the rest of the pipeline.
We built HXG1 to change that, and to make deep analytics available on all bids, regardless of size or corporate priority.
Pricing expertise, built into the models
HXG1 combines the strategic frameworks we used on real federal competitions with machine learning, market data, and purpose-built analytical models.
That combination matters. Data science without domain expertise can find patterns without understanding what they mean. And domain expertise alone doesn’t scale.
HXG1 brings both together: models built around how federal competitions actually work, informed by practitioners who have spent their careers pricing them.
The goal is not to replace pricing judgment. It is to give pricing, capture, and executive teams a stronger analytical foundation for making decisions.
Better data. Better models. Experienced judgment. Built for real pricing decisions.
HXG1 gives teams an independent, data-driven view of competitive pricing. This analysis complements capture intelligence, allowing teams to understand where the market is likely to land, and make better decisions about how to position their bid.
Our objective is simple: make sophisticated pricing strategy and price-to-win available on every deal.