Superficial

Superficial is the audit layer for AI. It eliminates hallucinations and makes large language models reliable for high-stakes, real-world applications.

In regulated, high-risk environments, unverifiable AI outputs aren’t just inaccurate – they’re a liability. Superficial removes hallucinations with high precision claim extraction and verification. It is built for auditability, traceability and compliance.

Validated against Google DeepMind’s FACTS Benchmark, Superficial delivers:

• 99.5% one-shot factual accuracy across major models
• Enterprise controls to flag edge cases with precision
• Configurable workflows for complete hallucination elimination

Superficial works in real time. It:

• Extracts granular atomic claims from AI output
• Grounds each claim against public sources, private documents or internal databases
• Verifies claims using customised neurosymbolic reasoning
• Applies corrections and flags unverifiable content, with every change fully logged

The result is end-to-end provenance and source attribution for every model output – aligned with traceability, transparency and accountability principles in global regulations such as the EU AI Act.

Superficial is available via API, tailored enterprise offering and consumer web app. Its developer-first API supports training and production environments. It helps businesses verify AI-generated content and eliminate hallucinations with speed, scale and control.

The enterprise offering enables full hallucination elimination across organisations. It includes custom controls, SLAs and compliance-ready audit trails.

The web app allows users to eliminate hallucinations from any AI output. Corrections can be applied with no setup or integration required.