TaxRock announced the launch of TaxRock 2.0, introducing an AI-powered approach to managing IRS exposure that moves organizations beyond reactive monitoring.

Most teams managing IRS exposure aren't failing to do the work — they're operating within systems built around periodic transcript retrievals, filing events, and IRS notices that often arrive long after an underlying issue begins to develop. This creates extended periods of increasing risk with limited visibility.

TaxRock 2.0 builds on a prior generation of the platform that operates inside live production environments. Over time, hundreds of businesses and professionals used the system, stress-tested its capabilities, and identified improvements.

What emerged was a consistent pattern. Anyone managing IRS exposure at scale was running into the same blind spots: lenders underwriting against stale data, payroll companies with limited insight into client compliance, and tax professionals juggling hundreds of accounts manually. Different roles, same underlying problem.

They were not asking for more reports or additional alerts. They wanted earlier awareness — and a way to remain focused on what matters most without constant manual review.

TaxRock 2.0 reflects the result of following those patterns to their logical conclusion. The platform replaces snapshot-based monitoring with continuous visibility into IRS account activity.

Building on prior operational experience, TaxRock rebuilt the platform from the ground up, embedding AI directly into its core architecture.

At the center of the platform is Rocky, TaxRock's AI assistant — a tax-specific intelligence layer built for risk management at scale. It surfaces issues across hundreds of accounts, elevating the most urgent signals and enabling teams to prioritize intervention where it is most needed.

"We didn't start with a pitch deck — we started with a problem, and it turned out everyone managing IRS exposure had it," said Ron Jost, Founder & CEO of TaxRock. "TaxRock 2.0 reflects years of solving that problem in practice and then rebuilding the platform with AI embedded at its core."