Medeloop

What is Medeloop?

Medeloop is a clinical research analytics platform that helps healthcare professionals, researchers, and life sciences teams turn complex patient data into meaningful research evidence. It uses AI agents to support study planning, patient cohort identification, statistical analysis, and report generation. Researchers can describe questions in plain language, review proposed study methods, and generate traceable outputs using supported real-world healthcare data or their own datasets.

Medeloop is a clinical research technology company co-founded by Rene Caissie and Josh Walonoski. Its Analytics platform supports research using electronic health records, insurance claims, registries, and other clinical datasets. The official website advertises access to more than 200 million patient records through its current pricing offering, alongside research workflows that produce cohorts, statistics, figures, and manuscript-ready reports. Researchers can begin with a free option offering 3 threads, according to the pricing page. No coding is required to start exploring its workflow.

• Platform Focus: Agentic clinical research intelligence, real-world evidence (RWE) analytics, federated healthcare data execution, and automated cohort building
• Developer / Entity: Medeloop Inc.
• Launch Year: AI Clinical Intelligence Platform

Use Cases:

• Conducting comparative effectiveness research, treatment pattern tracking, and healthcare resource utilization analyses
• Building and characterizing complex patient cohorts from structured EHR, claims, and disease registry data
• Executing federated queries on institutional data without exporting raw, protected health information (PHI)
• Generating publication-grade statistical tables, review-ready figures, and STROBE-compliant manuscript drafts
• Analyzing preloaded research-grade real-world data (38M+ de-identified patient claims via HealthVerity)

Technology:

• Agentic AI pipeline coordinating query understanding, feasibility checks, protocol drafting, and query execution
• Semantic code engine mapping plain-language clinical concepts automatically to ICD-10, CPT, NDC, and SNOMED code sets
• Federated execution architecture running locally within AWS, Azure, GCP, or on-premise health system infrastructure
• Native data parsing engine operating directly on raw EHR and claims schemas without requiring prior OMOP harmonization

Target Users:

• HEOR, clinical R&D, and biopharma teams at life sciences and biotech companies
• Clinical researchers, epidemiologists, and faculty at academic medical centers (e.g., Stanford, Duke, Cedars-Sinai)
• Health system administrators, CROs, and population health management teams

Corporate Entity: Operates as Medeloop Inc. / medeloop.ai

Key features of Medeloop

Medeloop's key features are

• Plain-Language Clinical Queries: Submit natural language questions to automatically generate structured research protocols and code sets.
• Federated Data Execution: Runs validated analytical queries locally within your cloud or on-premise infrastructure without moving raw patient data.
• Semantic Concept Engine: Automatically maps clinical concepts to standardized medical vocabularies (ICD-10, CPT, NDC, SNOMED).
• Automated Feasibility Assessment: Checks cohort size, statistical power, and data coverage before initiating full study execution.
• Publication-Ready Outputs: Delivers versioned research objects, Kaplan-Meier curves, regression tables, and auditable manuscript drafts.
• Preloaded Real-World Dataset: Instant access to 38M+ de-identified all-payer claims records for teams without proprietary data.

Medeloop Pricing

Medeloop operates on a freemium self-service model alongside enterprise and institutional license tiers.

Free Plan / Starter Exploration:

• $0 / Free Trial Access
• Allows researchers to test natural language queries, explore preloaded real-world datasets, and run basic feasibility checks

Enterprise & Institutional Plans:

• Custom enterprise subscription pricing for health systems, pharma, and academic institutions
• Includes custom federated deployment behind corporate firewalls, custom schema integration, unlimited query runs, and dedicated support

Who is using Medeloop?

Medeloop is used by clinical and health economics researchers at top institutions, including

• Academic Medical Centers: Stanford Medicine, Duke, Cedars-Sinai, UC San Diego, McGill University, and University of Missouri
• Pharmaceutical & Life Sciences R&D Teams: Conducting rapid real-world evidence (RWE) and comparative effectiveness studies
• Health Systems & Public Health Agencies: Analyzing population health trends and care delivery metrics

Best Medeloop Alternatives

Some of the strongest Medeloop alternatives include

• TriNetX
• Aetion Evidence Platform
• Komodo Health
• Truveta
• Nested Knowledge
• Atropos Health

Pros and Cons of Medeloop

Pros

• Federated architecture ensures protected patient data never leaves local institutional firewalls
• Eliminates months of Common Data Model (OMOP) conversion by natively parsing raw EHR and claims data
• Dramatically cuts clinical research turnaround times from weeks or months down to hours
• Transparent human-in-the-loop workflow with full audit trails and inspectable statistical choices

Cons

• Custom enterprise federated deployment requires coordination with IT and data governance teams
• Statistical outputs and manuscript drafts require clinical review prior to peer-reviewed submission
• Specialized focus on retrospective clinical and observational real-world evidence rather than prospective trial recruitment

Why Choose Medeloop?

Medeloop is an ideal choice for healthcare systems, pharmaceutical teams, and clinical researchers who want to execute rapid real-world evidence studies on raw EHR and claims data without sacrificing data privacy or clinical rigor.

• Converts plain-language medical questions into validated, auditable research outputs
• Keeps data secure using federated execution behind your organization's firewall
• Bypasses long OMOP conversion timelines with native semantic parsing
• Delivers publication-ready figures, statistical tables, and manuscript narratives

Medeloop vs. Competitors

The main difference between Medeloop, TriNetX, Aetion, and Komodo Health is that Medeloop uses an agentic AI architecture that natively parses raw EHR/claims data without requiring prior OMOP harmonization and executes queries via federated compute, whereas TriNetX relies on a standardized global network with OMOP mapping, Aetion specializes in formal regulatory-grade pharmacoepidemiology workflows, and Komodo Health focuses on a centralized commercial healthcare map. Medeloop stands out for its fast plain-language interface and federated execution.

How do we rate Medeloop?

Medeloop Review

Medeloop is a game-changing platform for clinical research intelligence. By replacing slow, manual database queries with an agentic AI system that understands natural language, maps clinical codes, and executes federated queries directly on native datasets, it reduces study turnaround times from weeks to hours. Its privacy-first federated architecture and transparent audit trails make it a top choice for health systems and life science teams.

Conclusion

Medeloop is a useful option for clinical researchers, pharmaceutical companies, healthcare organizations, and academic institutions seeking to simplify data-driven research. Its AI-assisted study planning, cohort analysis, statistical reporting, and traceable workflows can reduce repetitive tasks while supporting research transparency. Its flexible data architecture is another advantage for organizations working with different clinical datasets. Before adopting the platform, evaluate pricing, data compatibility, security requirements, and analytical validation to determine whether it fits your research objectives.