ToneGap

ToneGap audits deployed voice agents for bias before your customers ever encounter it. We tested a job screening agent with four synthetic voices delivering identical scripts—and discovered systemic disparities: one speaker's employment-gap disclosure survived only 50% of calls despite being spoken verbatim. Female voices were interrupted in every single call (100%), while male voices faced zero interruptions. An acoustic emotional analyzer detected a 64-percentage-point anger-confidence gap across demographic groups despite vocal delivery. This isn't theoretical. When voice agents screen candidates, approve loans, or triage healthcare, these artifacts become permanent records that disqualify people. ToneGap runs as a pre-deployment gate: your agent gets tested, you get the receipts (tool calls, transcripts, interruption timelines), and you can fix issues before deployment. Built on AssemblyAI Voice Agent API's session artifacts—harvesting tool calls, transcripts, and conversation metadata—we export compliance-ready evidence packages. For enterprises deploying voice AI in regulated industries, this is the audit trail you need when auditors ask: "Did your agent treat everyone equally?"