Code-first engineering intelligence startup Flux Cyber Inc. today expanded its platform with tools meant to show engineering leaders whether their investment in artificial intelligence for software development is paying off.
The release takes on a problem Flux says has come up again and again with engineering leaders over the past year. Adoption is easy enough to show. What most of them still report upward, according to the company, are tickets, story points, sprint velocity and token counts, which describe how busy a team has been more than what it delivered.
Research from Google Cloud’s DevOps Research and Assessment program suggests adoption alone says little about results. Its 2025 report found 90% of software professionals using AI at work. On whether that makes teams better, the authors wrote that AI “doesn’t fix a team; it amplifies what’s already there.”
Ted Julian, founder and chief executive of Flux, called AI “the biggest bet most engineering organizations have ever made.” The blind spots undermining that bet, he said, hide inside tools built for a different era of software development. “Tickets and adoption rates describe intent,” Julian said. “The code itself shows what the team actually built and delivered.”
Flux has broken the problem into five blind spots, each with a capability of its own. All five capabilities run on the code analysis the platform already performs, so customers do not have to add instrumentation or change how their teams work. Each blind spot is assessed separately, because an organization can be solid in one area and exposed in another.
The first goes after what Flux calls velocity theater. Verified velocity sorts each merged change by type, from new features to bug fixes, and deployment frequency and lead time are then measured against the organization’s own history. A burst of activity counts as progress only when the code backs it up.
Review debt is the second target. Trusted review tracks how long changes wait for a first reviewer and how the load is spread, then weighs review depth against each change’s size and risk. The point is to spot a backlog before it lands on a few overstretched senior engineers. A third capability, auditable work, pulls activity straight from commits and pull request history, so significant changes show up under a name even when nobody touched a ticket.
A fourth, continuous quality, follows new and resolved security findings, newly added dependencies and failure and recovery trends against each team’s norms, with the aim of catching drift before it causes a production incident.
The last capability is built as much for finance as for engineering. Defensible spend sorts work into capitalizable and operational categories. Flux said that gives leadership something solid to point to for spending decisions and research and development tax credits. Token usage does not enter into it, since the measure is engineering effort and where it goes.
All five capabilities are generally available now.
Flux is backed by venture capital. Calibrate Ventures led its $5 million round in June, when True Ventures and Glasswing Ventures also invested.
