Klinische KI, verankert in Fakten – nicht in Halluzinationen.
Die meisten KI-Schreiber erstellen Notizen direkt aus einem Transkript und hoffen, dass das Modell nicht improvisiert. Die patentgeschützte FactsContext™-Engine von Notat versteht zuerst die Begegnung: Sie extrahiert strukturierte klinische Fakten, generiert daraus die Dokumentation und zeigt Ihnen die Rohfakten, damit Sie diese ganz nach Belieben nutzen können. Sie funktioniert in der echten multilingualen Versorgung: Sprachaufnahme in über 99 Sprachen und ein Produkt, das in 15 Sprachen übersetzt ist.
Versteht, bevor es schreibt
FactsContext™ trennt das Verständnis vom Schreiben. Diese Trennung ist es, was die Dokumentation vertrauenswürdig macht – und was jede nachfolgende Funktion ermöglicht.
1. Conversation
The encounter happens naturally. Notat listens ambiently — no dictation, no prompts, no screens between you and the patient.
2. Clinical facts
FactsContext™ extracts structured clinical facts from the conversation: symptoms, findings, medications, decisions, plans. Each fact is anchored to what was actually said.
3. Documentation
The note is generated from the extracted facts — never straight from a raw transcript. If a statement isn’t supported by a fact, it doesn’t belong in the note.
4. Review
You see the raw facts next to the note. Verify any sentence against its source, edit what you want, and sign with confidence. The clinician always remains in control.
Radikale Transparenz: Sie sehen die rohen Fakten
Vertrauen ist kein Versprechen – es ist etwas, das man überprüfen kann. Notat macht den strukturierten medizinischen Kontext hinter jeder Notiz sichtbar, sodass die Frage „Woher kommt dieser Satz?“ immer eine Antwort hat.
The facts are yours
Notat shows you the raw extracted medical facts from every encounter — not just the polished note. Inspect them, verify the note against them, or reuse them however you please.
Every sentence is traceable
Because documentation is generated from structured facts, every statement in the note traces back to something that actually happened in the encounter.
Nothing invented
Transcript-direct AI fills gaps with plausible-sounding text. FactsContext™ is designed to reduce unsupported statements by only writing from verified clinical facts.
Alles aufgebaut auf einem klinischen Verständnis
Da FactsContext™ strukturierte Fakten erzeugt – nicht nur eine Notiz – treibt dasselbe Verständnis der Konsultation jede Funktion in der Plattform an.
Clinical notes
SOAP, H&P, progress notes — written from facts in your style.
ICD-10 coding
Code recommendations with the supporting evidence excerpt attached.
Referral letters
Generated from the same clinical understanding, not re-dictated.
Magic Edit
Rewrite, translate, or restructure — the facts stay the source of truth.
Patient instructions
Plain-language follow-up built from what was actually decided.
Evidence answers
Clinical questions answered in the context of the encounter facts.
Validieren Sie die Architektur
FactsContext™ verbindet die Beweismethodik, Anbietervergleiche, ICD-10-Evidenz und mehrsprachige Workflows mit derselben faktenorientierten Architektur.
Clinical AI evaluation
See the transparent methodology Notat uses to evaluate unsupported statements, fact coverage, and correction burden.
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Compare AI scribes
Review dated vendor comparisons across hallucination safeguards, languages, compliance, and EHR fit.
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ICD-10 evidence
Explore condition guides and code suggestions that attach evidence excerpts to recommended codes.
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Multilingual scribe
See 99+ spoken-language capture and translated workflows for cross-language care.
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Häufig gestellte Fragen
What is AI hallucination in healthcare documentation?
Hallucination is when an AI writes plausible-sounding statements that were never said or observed — an invented medication dose, a symptom the patient never reported, a plan that was never discussed. In clinical documentation, unsupported statements are a patient-safety and legal problem, not just a quality problem.
How does FactsContext™ reduce hallucinations?
Most AI scribes generate notes directly from a transcript, which lets the language model improvise. Notat’s patent-pending FactsContext™ engine works in two distinct stages: it first extracts structured clinical facts from the encounter, then generates documentation only from those facts. Statements without a supporting fact are designed not to appear in the note.
Can I see the facts behind my note?
Yes. Notat shows you the raw extracted medical facts alongside the generated note. You can verify any sentence against its source facts before signing, and reuse the facts for coding, referrals, or anything else.
Does the clinician still review the note?
Always. FactsContext™ makes review faster and safer because you can check the note against structured facts instead of re-listening or guessing — but you review and sign every note. The AI does the writing; you do the medicine.
Does FactsContext™ work in my language?
Yes. Notat supports spoken capture in 99+ languages through its AssemblyAI-powered speech layer, and the product is translated in 15 languages: English, Norwegian, Danish, Swedish, Finnish, Estonian, Dutch, German, Spanish, Italian, French, Arabic, Polish, Portuguese, and Hindi. The conversation, the extracted facts, and the final documentation can each be in different languages, including cross-language visits where the patient and the record don’t share a language.
Sehen Sie die Fakten hinter Ihrer nächsten Notiz.
Nehmen Sie eine Konsultation auf, beobachten Sie, wie FactsContext™ die klinischen Fakten extrahiert, und lesen Sie eine Notiz, die Sie Zeile für Zeile verifizieren können. Sie prüfen und signieren jede Notiz – Notat macht das einfach mühelos.
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