Evidently is a Cognitive AI platform that automates the extraction and summarization of clinical data using a Knowledge Graph and Machine Reading technology, enhancing documentation, clinical decision support, and research processes. By streamlining low-level cognitive tasks, it reduces clinician workload, minimizes errors, and improves patient care efficiency, ultimately leading to better reimbursement outcomes.
Funding
$23.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Clinicians spend a significant amount of time reviewing patient charts and clinical data within electronic health record (EHR) systems. EHRs organize data by source and modality, which forces clinicians to sift through large volumes of unstructured data, leading to inefficiencies, increased workload, and potential errors in clinical decision-making, documentation, and research.
Solution
Evidently offers a cognitive AI platform that automates the extraction, structuring, and summarization of clinical data from EHRs. The platform uses machine reading and a medical knowledge graph to transform unstructured data into problem-oriented views, providing clinicians with concise summaries of patient information and relevant clinical knowledge. By integrating directly into existing EHR workflows as a SMART on FHIR application, Evidently reduces the burden of manual chart review, improves documentation accuracy, accelerates clinical research, and supports population health initiatives. The platform enables proactive clinical decision support, comprehensive documentation integrity, rapid trial matching, and in-depth analytics for care gap identification and risk stratification.
Target Audience
Evidently targets physicians, clinical documentation improvement (CDI) specialists, clinical research teams, and healthcare organizations focused on value-based care and population health management.
Features
- EHR-embedded application accessible within Epic, Cerner, and Athenahealth via SMART on FHIR integration
- Machine reading engine that extracts and interprets unstructured data from clinical notes, reports, and scanned documents
- Medical knowledge graph encoding millions of medical concepts and their relationships
- Automated summarization of patient data into problem-oriented views (POVs)
- Proactive clinical decision support with real-time access to relevant clinical knowledge
- Automated HCC/CC/MCC capture for improved documentation integrity and reimbursement
- Real-time deep phenotyping for accelerated clinical trial matching
- Omnivorous analytics for care gap identification, risk stratification, and cost reduction in population health management