Detect and fix hallucinations in AI outputs with an automated verification layer

Detect and fix hallucinations in AI outputs with an automated verification layer targets a $12.0B = 10M businesses × $1.2K ACV total addressable market with medium saturation and a year-over-year growth rate of 40% YoY (source: McKinsey & Company and CB Insights reports on generative AI adoption and enterprise AI spending).

Key trends driving demand: LLM adoption across enterprise workflows is accelerating — as more teams automate text and decision tasks, demand for post-generation verification increases.; Regulatory and internal governance initiatives are forcing companies to require provenance, audit logs, and explainability for AI outputs, creating procurement demand.; Hybrid verification approaches (retrieval + model ensembles + rule validators) are becoming practical as API costs fall and retrieval tooling improves, enabling effective accuracy layers..