What is Mendel?

Mendel provides an advanced AI platform engineered to replicate the cognitive processes of physicians, enabling users to extract valuable insights from complex clinical data. By integrating large language models with its proprietary clinical Hypergraph technology, the platform delivers clinically trustworthy answers. It ensures results are based on a comprehensive view of the patient's journey, consolidating information from diverse structured and unstructured data sources, while actively guarding against inaccuracies and hallucinations by grounding outputs against the clinical hypergraph.

The platform features a suite of AI copilots known as Hypercubes, designed to enhance various clinical workflows. These tools facilitate rapid cohort gathering based on multifaceted criteria, visualize complex data interactions, navigate and analyze intricate datasets for improved decision-making, and de-identify Protected Health Information (PHI) from clinical records. Mendel also offers the flexibility to build custom copilots tailored to specific data challenges and integrates seamlessly with existing BI, ETL, and data ingestion tools, ensuring data security and compatibility.

Features

Clinical Reasoning AI: Mimics physician-level cognitive abilities using LLMs and a clinical Hypergraph.
Hypercube Copilots: A suite of AI agents for specific clinical workflows (Cohort, Charts, Analyst, Redact, Build Your Own).
Cohort Retrieval: Swiftly gather patient cohorts based on complex criteria.
Chart Review & Visualization (Charts Copilot): Visualize complex data interactions and trends from clinical records.
Clinical Data Analysis (Analyst Copilot): Navigate and analyze complex datasets using SQL-based analytics.
PHI De-identification (Redact Copilot): Redact Protected Health Information from clinical records for privacy and compliance.
Longitudinal Patient View: Consolidates diverse data sources for a coherent patient journey.
Explainable & Verifiable Results: Provides supporting evidence for all generated responses.
Integration Capabilities: Connects with existing BI, ETL, data ingestion tools, and supports various LLMs.
Custom Copilot Building: Allows users to create tailored AI copilots for specific needs.

Use Cases

Accelerating clinical trial prescreening.
Improving patient cohort identification for research.
Enhancing clinical chart review accuracy and efficiency.
Streamlining prior authorization processes for providers.
Matching patients to suitable clinical trials.
Extracting insights from unstructured diagnostic data (e.g., pathology reports).
Optimizing clinical data analytics workflows.
Commercializing Real-World Data (RWD) assets.
Ensuring PHI compliance through automated redaction.
Developing custom AI solutions for specific clinical data challenges.