Vaudit, the company building an independent verification layer across AI, cloud and enterprise billing, today launched TokenAudit to help companies audit AI bills against contract terms and recover money when billing errors occur. Since March, Vaudit has reviewed $34 million in AI spending across 60 companies and identified nearly $1.7 million in mistaken overcharges, with roughly 80% credited back by providers or cloud platforms, including AWS, Google Cloud, Microsoft Azure, Anthropic and OpenAI.
Vaudit reviews $34M in AI spending, identifies $1.7M in overcharges, 80% credited back.
Worldwide AI spending projected to reach $2.59T in 2026, up 47% YoY.
Five recurring billing error patterns identified including premium rate billing, retry storms, and outage billing.
Customers install SDK to capture raw usage data and reconcile against invoices.
Current customers include Panasonic, HP, and Honda.
Vaudit has audited $1.2B+ in vendor spend, recovered $50M+.
Worldwide AI spending is projected to reach $2.59 trillion in 2026, up 47% year over year, with AI infrastructure expected to account for more than 45% of total spend, according to Gartner. But as enterprises scale AI adoption across multiple model providers, model versions, and cloud platforms, billing is becoming harder to verify. Each vendor calculates usage inside its own system, leaving finance and engineering teams without a clear way to confirm whether invoices match what was actually used. The problem is becoming more urgent as "tokenmaxxing" moves from an engineering quirk to a business risk.
Vaudit customers install a software development kit inside their AI environment to capture raw usage data, reconcile it against invoices and flag discrepancies. The company has traced billing errors to five recurring patterns: customers billed at premium rates for cheaper or older models; prompts that returned no output but were billed anyway; "retry storms" where autonomous agents repeat a failed request and rack up duplicate charges; billing that continued through provider outages; and orchestration errors where a cloud provider sends the same request to two models at once. Roughly half of the billing decisions run through cloud providers rather than directly through model providers, with clear-cut errors typically credited back within 48 to 96 hours.
Michael Hahn, founder and CEO of Vaudit, stated: "What we are observing is that enterprise AI billing has become increasingly opaque. Customers often don't have independent visibility into which model actually handled a request, how it was routed, or whether it was cached, retried or deduplicated before it showed up on their bill."
Omar Hamoui, partner at Mucker Capital, added: "Enterprises are scaling AI faster than their finance teams can verify what they're being billed for, and that gap only widens as agents drive more usage. We backed Vaudit because independent auditing of AI spend is becoming essential infrastructure, and TokenAudit puts real accountability behind a budget line growing faster than almost any other."
TokenAudit is the newest addition to a three-product platform that also includes Vaudit's original ad-spend audit and an all-vendor audit layer covering cloud, SaaS and other categories. TokenAudit extends Vaudit's existing approach into one of the fastest-growing enterprise spend categories: AI. The company is independently verified for GDPR, CCPA, SOC 2 Type 2 and ISO 27001:2022 compliance.
About Vaudit
Vaudit is an independent auditing and recovery platform for enterprise vendor spend, covering AI tokens, digital advertising, cloud and other major vendor categories. Its fleet of AI agents continuously verifies charges, enforces billing guardrails and recovers money when bills don't match contracts or usage. Vaudit has audited more than $1.2 billion in vendor spend and recovered more than $50 million for clients, including Panasonic, HP, Honda and Traffic Guard. Founded in 2023 and based in San Francisco, California, the company is independently verified for GDPR, CCPA, SOC 2 Type 2 and ISO 27001:2022 compliance.
