A SaaS quality-control layer that audits AI-generated clinical documentation for accuracy, completeness, safety, and language-specific issues before EHR submission.
Added Jun 13, 2026
Last signal 1d ago
Healthcare organizations are rapidly adopting AI assistants to reduce documentation burden, but clinical notes now span many care settings, countries, and languages. Teams need a way to catch hallucinations, missing details, unsafe phrasing, and workflow gaps before AI-generated documentation becomes part of the medical record.
The product integrates with AI documentation tools and EHR workflows to review generated notes against visit transcripts, specialty templates, and clinical safety rules. It flags risky or incomplete sections, tracks documentation quality by language and care segment, and gives product, clinical, and operations teams a dashboard for model performance and compliance monitoring.
AI clinical documentation is moving from pilots to massive weekly usage across global healthcare systems. As adoption scales, buyers will need independent QA and monitoring tools around the AI care assistants they deploy.
70
82% score confidenceTrend snapshot pending
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What we’re about At Harrison.ai (formerly known as Annalise.ai ), we’re redefining what’s possible in healthcare. Through our diagnostic AI solutions, we’re building tools that support clinicians to deliver earlier, more accurate diagnoses and raise the standard of care for millions of patients worldwide.
We pivoted from broad healthcare AI to building Earth's finest AI Care Partner. Today, we support over 2 million patient sessions weekly across 116 countries and over 110 languages. Hundreds of thousands of clinicians use Heidi to complete documentation.
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