Built by people who know government contracting from the inside
HXG1 was built by pricing subject matter experts, data scientists, and software developers who have spent their careers inside federal contracting.
Our pricing and strategy experience spans the full GovCon market. We have supported companies with fewer than fifty employees and companies with revenues in the billions. We have led pricing, price-to-win, and competitive strategy on task orders under ten million dollars and on managed services programs worth several billion. We have worked recompetes, new competition, IDIQ and BPA vehicles, strategic captures, and enterprise-scale procurements across defense, civilian, and intelligence customers.
On the largest and most complex pursuits, we have worked on strategy years before an RFP was released: shaping pricing structures, evaluation models, and acquisition strategy directly with customer stakeholders during the earliest phases of program development. By the time those opportunities reached the street, the pricing strategy was already grounded in deep customer context and market analysis that most competitors would only begin assembling at RFP release.
That range matters because pricing strategy is not one discipline. The analytical approach that wins a focused task order on a best-value BPA is fundamentally different from the approach that wins a multibillion-dollar enterprise recompete evaluated on lowest price technically acceptable. We have worked both ends and most of what falls between.
Why that background produced HXG1
Most pricing and price-to-win work still runs on manual research, disconnected spreadsheets, and institutional knowledge that disappears when people move on. Experienced teams can produce strong analysis, but the process does not scale. And the market data that should inform every bid is too large and too fragmented for any analyst to review by hand.
We built HXG1 because we kept seeing the same high-value analytical work reconstructed from scratch on every pursuit. The questions recur. The data exists. What was missing was a machine learning layer that could make that data usable at the speed and consistency that pricing teams actually need.
Our role
HXG1 is a decision-support platform, not a replacement for the people who make pricing calls. Our goal is to give capture, pricing, and executive teams a stronger analytical foundation, so that cutting edge financial prediction models and expert judgment are available on every bid.