Machine learning brings understanding and follow-through to medical conversations.

verb: shorten (a piece of writing) without losing the sense.

Our industry-leading research powers automated solutions for thousands of clinicians today.

The Highlights

What We’re Building

AI that summarizes medical conversations and extracts structured data for coding, billing, and risk assessment.

Rigorously tested modular pipelines that make it easy to customize the AI to your needs.

Proprietary and de-identified dataset of 1.5M+ medical encounters.

More peer-reviewed publications than any other entity in the field of medical conversation understanding.


We are a diverse team of experts in machine learning, including Carnegie Mellon University professors and their respective labs.

Elisa Ferracane, PhD

Abridge - ML Research

Florian Metze, PhD

Abridge - Advisor, Co-Founder Carnegie Mellon University - Research Professor

Katerina Fragkiadaki, PhD

Carnegie Mellon University - Assistant Professor

Kundan Krishna

Carnegie Mellon University - PhD Student

Nathan Price

Abridge - ML Research

Nimshi Venkat Meripo

Abridge - ML Research

Sai Prabhakar

Abridge - ML Research

Shruti Palaskar

Carnegie Mellon University - PhD Student

Zack Lipton, PhD

Abridge - Scientific Advisor Carnegie Mellon University - Assistant Professor


Contributions to Research

ASR Error Detection via Audio-Transcript entailment

Nimshi Venkat Meripo and Sandeep Konam

Interspeech 2022 Special Session, Speech and Language in Health: from Remote Monitoring to Medical Conversations

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Weakly Supervised Medication Regimen Extraction from Medical Conversations

Dhruvesh Patel, Sandeep Konam and Sai Prabhakar

3rd Clinical Natural Language Processing Workshop, The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

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Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations

Benjamin J Schloss, Sandeep Konam

Proceedings of Machine Learning Research, Machine Learning for Healthcare (MLHC) 2020

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ASR Error Correction and Domain Adaptation Using Machine Translation

Anirudh Mani, Shruti Palaskar, Nimshi Venkat Meripo, Sandeep Konam, Florian Metze

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing

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