Mendel.ai
Contact for pricing
Overview
Mendel.ai offers an AI-powered platform designed to enhance clinical data workflows for life sciences and healthcare organizations. Its core technology combines large language models with a proprietary clinical hypergraph to facilitate scalable and explainable clinical reasoning. This approach aims to structure complex clinical data, reconcile conflicting information, and generate comprehensive patient journeys.
- What it does: Mendel.ai extracts, structures, and analyzes complex clinical data, providing automated clinical reasoning with explainable outcomes. It aims to eliminate AI hallucinations, which is intended to reduce risk in sensitive healthcare environments.
- Who it is for: The platform serves life sciences organizations, academic institutions, and clinical researchers. It is relevant for specialties involved in clinical research, drug development, and patient cohort identification, particularly in areas like oncology.
- How it fits a clinical or practice workflow: Mendel.ai’s tools, such as Hypercube Copilots and Hypercube Analyst, are designed to streamline tasks like patient chart reviews, identify patient cohorts for clinical trials, and accelerate queries on clinical data. It can assist in identifying candidates for novel therapeutics and customizing AI copilots for specific data needs, including EMR-to-registries and site activations.
- Notable capabilities: Key capabilities include 100% explainability of AI outcomes and the ability to reason over large datasets without hallucinations. The platform can process and understand complex, unstructured medical data at scale, offering a neuro-symbolic reasoning system built for clinical data workflows. It also offers a chat interface, Hypercube, for natural language querying of clinical data.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Neuro-Symbolic AI
- Structured & unstructured EHR data processing
- Automated patient cohort identification
- Clinical trial matching
- Real-world data analysis
- Disease progression modeling
- Treatment pathway analysis
Use Cases
- Accelerating clinical trial recruitment
- Identifying eligible patients for studies
- Analyzing real-world evidence for research
- Optimizing trial design
- Understanding disease epidemiology
- Supporting drug development
What Physicians Need to Know
Evidence Base
Mendel.ai's platform leverages large language models (LLMs) coupled with a proprietary clinical hypergraph, which is a multi-dimensional knowledge graph based on knowledge representations from enriching and structuring medical information and relationships. This approach allows their AI to decipher clinical data with clinician-like logic by indexing structured and unstructured data from original medical records and clinical literature. They aim to learn from the journeys of hundreds of millions of patients to make medicine more objective and intelligent.
Clinical Validation Studies
Mendel.ai has conducted studies demonstrating the effectiveness of its Neuro-Symbolic AI system. One study, in collaboration with the University of Pennsylvania, evaluated the use of AI-augmented software alongside human review for clinical data extraction in oncology patient pre-screening for clinical trials. It found improved accuracy and timeliness, with human-AI teams being noninferior to human alone (78.7% vs. 76.7%) and both superior to AI-alone (63.5%) among 74 patients. Another trial, 'ACR: A Benchmark for Automatic Cohort Retrieval,' conducted with Cornell University, showed Mendel's Neuro-Symbolic system outperformed GPT-4 in sorting patient cohorts from EMRs, highlighting the potential of integrating expert knowledge with LLMs in healthcare. A study comparing Mendel's Neuro-Symbolic AI system against traditional SQL queries with SNOMED CT data models found a 10x increase in efficiency, a 90% reduction in query error rate, and over 80% cost reduction.
Alert Fatigue Management
While Mendel.ai's core focus is on clinical reasoning and data abstraction, AI-powered tools in general address alert fatigue by prioritizing and contextualizing alerts, filtering out irrelevant notifications, and continuously learning to improve accuracy. This helps clinicians focus on critical issues and reduces the desensitization caused by an overwhelming number of alerts.
Differential Diagnosis Support
Mendel.ai's AI deciphers clinical data with clinician-like logic, indexing structured and unstructured data to enable healthcare workers to interface with patient data using natural language. This capability, combined with its clinical reasoning models, allows for a comprehensive understanding of patient journeys. While not explicitly detailed as a 'differential diagnosis' feature, the ability to holistically analyze patient records and provide deep insights into longitudinal patient journeys supports informed diagnostic decision-making. Other AI tools in the medical field, like Dx29, analyze patient phenotype and genotype to generate a ranked differential diagnosis.
Clinical Workflow Integration
Mendel.ai aims to streamline clinical data workflows and integrate its AI into the fabric of every healthcare data platform. Their Hypercube Copilots and Hypercube Analyst are designed to revolutionize clinical data workflows with advanced clinical reasoning capabilities, enabling tasks like identifying patient cohorts and streamlining clinical research participation. Mendel's platform integrates structured and unstructured data from EMRs into a single comprehensive record, using technologies like optical character recognition (OCR), named entity recognition, and machine learning. They offer AI co-pilots for different workflows, including file matching, prior authorization, and abstraction, and allow customers to build their own.
Decision Audit Trail
Mendel.ai's Neuro-Symbolic Reasoning System is built to ensure explainability and consistency in AI outputs, making it readable and reliable to medical practitioners. The system can offer clear recommendations to clinicians and transparently provide the reasoning behind those decisions, which is crucial for building trust. General AI audit trail requirements in healthcare include capturing a chronological, tamper-evident record of AI system decisions, inputs, outputs, actions, and the reasoning expressed in human-readable language. This supports accountability, risk management, and compliance with regulations like HIPAA.
Physician Tip
Leverage Mendel.ai's Hypercube Copilots and natural language interface to quickly identify patient cohorts, streamline chart reviews, and gain deeper insights from both structured and unstructured patient data. The system's explainable AI provides transparent reasoning for its recommendations, which can aid in validating decisions and building trust in the technology. Utilize the platform to accelerate clinical research participation and identify candidates for novel therapeutics.
Mendel.ai is built on AWS and collaborates with Google Cloud and Databricks, indicating a focus on robust cloud infrastructure and advanced AI/ML capabilities. They integrate with various data sources, including EMRs, to unify fragmented clinical data. The platform's design allows for customized AI Copilots and seamless querying across multiple data sources, suggesting strong integration potential within existing healthcare IT ecosystems.
Details
| Category | Clinical Decision Support & Reference, Drug Discovery & Research, Oncology AI |
| Pricing | Contact for pricing — unknown |
| Deployment | Cloud-based |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
Unknown AI-estimated Mendel.ai does not appear to have specific FDA clearance for its AI platform, as it primarily focuses on patient identification for clinical trials rather than diagnostic or treatment recommendations. |
| Integrations | |
| EHR | Not specified |
| Specialties | Hematology, Internal Medicine, Oncology |
What the Web Says
Mendel.ai is generally viewed as a powerful AI platform for oncology, praised for its ability to extract and synthesize complex patient data from various sources, aiding in clinical trial matching and personalized treatment. Reviewers highlight its potential to significantly reduce manual data abstraction and improve the efficiency of research and patient care in cancer treatment. However, some sources also point to the inherent challenges of integrating such advanced AI into existing healthcare workflows and the need for robust validation.
Overall: PositiveStrengths
- Automates data extraction from unstructured clinical notes and reports
- Accelerates patient identification for clinical trials
- Provides comprehensive, longitudinal patient profiles
- Supports personalized treatment recommendations in oncology
- Reduces manual data abstraction time and effort
- Potential to improve research efficiency and drug development
Limitations
- Integration challenges with existing EHR systems
- Requires significant data volume and quality for optimal performance
- Potential for 'black box' concerns common with complex AI
- Cost of implementation and ongoing maintenance
- Need for continuous validation and human oversight
- Limited public physician reviews available for specific user experience
Based on reviews from: TechCrunch, Fierce Healthcare, G2 (general AI/healthcare AI reviews), Capterra (general AI/healthcare AI reviews), Healthcare IT News, Reddit (general AI in healthcare discussions)
Last updated: 2026-09-03
Ratings & Reviews
No reviews yet. Be the first to review this tool!
Rate Mendel.ai
Press & Coverage
Clinical Trials Arena
Mendel sees positive results in AI cohort matching trial
Mendel's Neuro-Symbolic AI system outperformed GPT-4 in a trial for sorting patient cohorts from electronic medical records, highlighting the potential of integrating expert knowledge with language learning models in healthcare. The study, titled 'ACR: A Benchmark for Automatic Cohort Retrieval,' was conducted alongside Cornell University.
2024-07
Business Wire
Mendel AI Joins NVIDIA Inception Program to Accelerate AI Innovations in Life Sciences
Mendel AI has joined the NVIDIA Inception program, gaining access to NVIDIA's technology and expertise to accelerate its Hypercube AI solution and bring sophisticated, reliable, and explainable AI to the healthcare sector. This collaboration aims to enhance Mendel's platform capabilities in processing complex, unstructured medical data.
2024-07
Medical Device Network
Mendel.ai software aims to save nurses time in pre-screening
A study by Mendel.ai and the University of Pennsylvania demonstrated that Mendel's AI software, used alongside nurses, improved the accuracy and timeliness of pre-screening oncology patients for clinical trials. The results, presented at ASCO 2024, showed that human-AI teams were non-inferior to humans alone in accuracy and improved timeliness.
2024-06
PR Newswire
Mendel Announces Collaboration with Snowflake and launches Hypercube, a Snowflake Native App
Mendel AI announced a collaboration with Snowflake, making its Hypercube Reasoning-Ready Product Suite generally available natively in the Snowflake AI Data Cloud. This integration allows customers to deploy Hypercube directly within the Snowflake environment, limiting data egress and enhancing clinical data workflows.
2024-09
Google Cloud
Can gen AI bring order to medical records? This startup is giving it a shot.
Mendel is using unique AI models and a clinical hypergraph to bring order to medical records, aiming to create comprehensive, accurate, and insightful patient journeys. A study found Mendel's Neuro-Symbolic AI system achieved a 10x increase in efficiency and an 80% cost reduction compared to traditional workflows with SNOMED CT.
2024-07
Business Wire
Mendel Launches Hypercube, an AI-Copilot for Real World Data Applications
Mendel launched Hypercube, an AI-copilot that enables life sciences and healthcare enterprises to interrogate patient data in everyday language through a chat-like experience. Hypercube uses a proprietary hybrid approach combining large language models with clinical reasoning to overcome limitations of traditional AI in healthcare.
2023-10
HMP Global Learning Network
Mendel AI: Enhancing Clinical Data Processing for Empowered Clinical Decision Making With Kristin Maloney, MS, BSN, RN, OCNu00ae, and Waqas Haque, MD, MPH
This article discusses how Mendel AI's neuro-symbolic AI system, combining large language models with proprietary clinical hypergraphs, enhances clinical data processing in oncology. It addresses challenges like unstructured data in EMRs and optimizes trial recruitment by providing a comprehensive view of the patient's journey.
2025-01
RARE Revolution Magazine
MendelScanu2014AI for good: informing patient and public perception
MendelScan, a rare disease case-finding platform, helps identify hidden clues in patient electronic health records to aid clinical decision-making and reduce time to diagnosis. The platform, a registered medical device, was a winner of the NHS AI Health and Care Award.
2024-10
Videos
Product demos, reviews, and walkthroughs for Mendel.ai.
Loading videos...
Frequently Asked Questions
Mendel.ai's AI platform, particularly its Hypercube feature, is designed to act as a co-pilot, augmenting human capabilities rather than replacing them. It helps physicians and nurses by accelerating tasks like pre-screening oncology patients for clinical trials, reviewing charts, and identifying patient cohorts by quickly navigating through extensive patient notes. This can lead to improved accuracy and timeliness in clinical data extraction and decision-making.
Mendel.ai emphasizes 100% explainability and aims to eliminate AI hallucinations, which are critical for trust and regulatory compliance in healthcare. The system stores data on the hospital side to address privacy concerns and integrates with various EMR systems. They also leverage a clinical hypergraph to ensure consistency and explainability in AI outputs, and their Neuro-Symbolic Reasoning System is built for clinical data workflows and analytics to limit hallucinations.
While Mendel.ai aims to overcome common AI limitations, AI systems generally still face challenges such as a lack of reasoning, potential for hallucination, and limited explainability. For example, AI might struggle to differentiate between abbreviations with multiple medical meanings without proper context. Additionally, integrating with fragmented clinical data across various EMR systems and building disease-specific ontologies can be complex.
Mendel.ai distinguishes itself by combining large language models with a proprietary clinical hypergraph, which allows for scalable clinical reasoning with high explainability and accuracy, aiming to eliminate hallucinations. Studies have shown that human-AI teams using Mendel.ai can be faster and no less accurate than humans alone for tasks like cancer data extraction. Its Neuro-Symbolic AI system has also outperformed general-purpose AI models like GPT-4 in cohort retrieval benchmarks.
Specific pricing details for Mendel.ai are not publicly available. However, similar AI agent platforms in healthcare can range from around $39-$129 per month for single agents, with enterprise contracts for more comprehensive suites. For detailed pricing, direct consultation with Mendel.ai would be necessary.
Competitors and alternatives to Mendel.ai in the healthcare AI and data management space include ConcertAI, Ciox Health, Carta Healthcare, and Solarity, which also offer AI suites and data processing products for the healthcare sector. Other AI platforms recommended by clinicians for various functions include DeepCura, Keragon, Microsoft/Nuance, Freed AI, Luma Health, and Innovaccer.
Mendel.ai's software is designed to integrate with almost every EMR system. The system stores data on the hospital side, which helps with privacy laws and eliminates the need for informed consent from Mendel.ai's perspective.
Suggest an Edit →
| Last Verified: 2026-09-03 | First Added: 2026-09-03