> ## Documentation Index
> Fetch the complete documentation index at: https://docs.corti.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Introducing FactsR™

> Real-time healthcare AI clinical reasoning system

FactsR is a real-time agentic reasoning system for clinical consultations. Designed with ambient documentation in mind, FactsR reduces general purpose AI driven “note bloat” by 65 percent, keeping records precise, relevant, and tightly aligned with the actual clinical conversation.

By minimizing post-visit edits and transforming passive transcripts into active clinical intelligence, FactsR sets a new benchmark for ambient AI in healthcare - while unlocking the path to real-time decision support at the point of care.

<Tip>To learn more about how to integrate with FactsR, check out [this guide](/textgen/extractfacts) or directly the API reference for [streams](/api-reference/streams/) and [extract-facts](/api-reference/facts/extract-facts).</Tip>

***

<iframe title="vimeo-player" src="https://player.vimeo.com/video/1092386417?h=415ef35296" width="640" height="360" frameborder="0" allowfullscreen />

## A Better Brain for Clinical AI

Unlike traditional LLM pipelines retrofitted for healthcare, FactsR is powered by Corti’s recursive fact-first reasoning loop - a purpose-built engine designed to surface, validate, and structure clinical knowledge in real time as conversations unfold.

Delivered as a modular API, it enables developers to embed clinical-grade intelligence directly into their healthcare applications - creating safer, leaner, and more trusted AI experiences at the point of care.

Rather than summarizing the full conversation in one go, FactsR breaks the task into three core stages:

1. **Extract** – Pull out clinically relevant facts in real time as the conversation unfolds.
2. **Refine** – Evaluate each fact using specialized reasoning agents to ensure accuracy, structure, and clinical relevance.
3. **Compose** – Build the final note using only validated facts, structured according to standard formats like SOAP.

This architecture doesn’t so much more than improve output quality, it transforms the documentation process.

<Card title="Corti's system already does an excellent job capturing clinical details accurately, even in natural conversation. But when testing this new innovation, what really stood out was the shift toward structured, recursive fact extraction. It goes beyond basic transcription to surface the right clinical facts in real time - exactly what busy clinicians need to stay focused and cut down on documentation overload." icon="quote">
  *Feedback from a beta user at Danish hospital*
</Card>

## Recursive Reasoning

Traditional ambient solutions pipe raw transcripts through generic models after the consultation has ended, producing verbose, error‑prone summaries that clinicians spend up to three hours a week correcting.

FactsR reflects a foundational shift in AI system design - from passive summarization to active reasoning. It allows developers to build AI that offers more concise, accurate results that clinicians can interact with live, in consultations and beyond.

The process unfolds in four key stages:

<Steps>
  <Step title="Listen and Extract in Real Time">
    As the consultation unfolds, FactsR continuously identifies and surfaces structured clinical “facts” - such as symptoms, vitals, medications, and social history - while the conversation unfolds, live.
  </Step>

  <Step title="Vet and Refine with Specialized AI">
    Each fact is automatically reviewed and improved through an AI-driven feedback loop. If something is unclear, the system refines it until it is accurate, consistent, and ready to use - no guesswork, no clutter.
  </Step>

  <Step title="Clinician-in-the-Loop">
    Clinicians can quickly review, accept, or adjust facts as they go. Early adopters report far fewer post-visit edits and rarely need to add missing information after the consultation. This design keeps clinicians in control, ensuring that AI augments rather than replaces clinical judgment.
  </Step>

  <Step title="Generate EHR-Ready Notes">
    Once the facts are finalized, the system assembles a clean, concise summary - free from long, verbose summaries or irrelevant content.
  </Step>
</Steps>

<iframe title="vimeo-player" src="https://player.vimeo.com/video/1092387099?h=e8c5bd689d" width="640" height="360" frameborder="0" allowfullscreen />

## Measured and Published

The innovation behind FactsR has been published together with evaluation results on the public benchmark Primock57 dataset. You can find the research paper [here](https://arxiv.org/abs/2505.10360). The evaluation shows that FactsR delivers -

* **49% reduction in missing clinically relevant content** (completeness errors drop from 23.3% to 11.7%)
* **86% reduction in extraneous detail** (conciseness errors fall from 14.3% to 2.0%)
* **Groundedness remains high at 94%**, comfortably above clinician reference notes

<Card title="More of what matters, far less of what doesn't" icon="badge-check">
  <Icon icon="check" /> **More Patient Focus** <br />Decisions stay in the consultation, not in hindsight.

  <Icon icon="check" /> **Less Screen Time** <br />Spend minutes, note hours, reviewing AI output.

  <Icon icon="check" /> **Audit‑Ready Transparency** <br />Every fact carries a timestamp, confidence score, and link back to the conversation.

  <Icon icon="check" /> **Healthcare AI that Delivers** <br />Real-time reasoning turbocharges ambient documentation, clinical decision support tools, and more.

  <Icon icon="forward" /> **Reduce cognitive load without sacrificing *control or trust***.
</Card>

<Info>You can also read the full announcement blog post [here](https://www.corti.ai/stories/introducing-factsr-the-thinking-engine-behind-better-clinical-ai).</Info>
