AI for Healthcare AnalyticsBuilt for the Complexity of Healthcare Data
End the backlog and stop choosing what questions get answered. Move fast with the AI solution built exactly for your analytics needs. Marmot collapses the time it takes to tackle your toughest questions into minutes, helping more patients find, start, and stay on the therapies they need.
The Two Things a Healthcare Data Platform Has to Get Right
Answers grounded in real patient data. Speed to patient impact.
The Data Foundation The Healthcare Map: Ground Truth for AI
Stop spending months reconciling conflicting healthcare data. The Healthcare Map brings open and closed claims-based events together into one trusted view of the complete patient journey, so you can make decisions sooner and deliver the right therapy to patients faster.
The AI-Powered Intelligence Layer Marmot: Say Yes to More, Maintain Less
Built specifically for the complexity of healthcare data, Marmot keeps your analysis capabilities current as technology evolves, so you stay focused on what matters most instead of reworking your AI every time a new model rolls out. Get all the upside of AI without the upkeep to speed insights to actual patient impact.
Inside a Healthcare Analytics Platform
The real-world data and AI infrastructure no healthcare analytics platform has matched.
Healthcare Analytics for Your Team
Commercial
Submit a request, wait two weeks, get a report built on data that already moved. Instead, ask Marmot a question and get a verified answer in the same session, with the method attached. Apps and custom agents handle the work your team repeats.
HEOR & Real-World Evidence
Answer the feasibility question while you can still change the study design. Marmot constructs the cohort, applies methods your team has already validated, and records every choice it makes. Reuse one definition across studies so two analysts reach the same answer.
Medical Affairs & KOL Strategy
KOL identification takes weeks of manual profiling, and MSL strategy gets built on incomplete pictures. Komodo finds the physicians actually influencing prescribing in your disease area, and traces journeys from diagnosis through treatment gaps in one session.
Clinical Development
Incomplete data doesn’t cost hours. It costs trial design decisions that can’t be undone. Size patient populations, model control arms against real-world treatment patterns, and assess site feasibility on actual patient concentration, before those decisions get made.
Evaluating a Healthcare Data Platform
Guides and benchmarks for teams evaluating healthcare data platforms, AI reliability, and real-world data analytics
What Trustworthy Healthcare AI Requires
Grounded, explainable, reproducible, verified, governed: the five pillars behind Marmot, and the engineering behind it.
The Five Pillars of Trusted AI
Komodo’s CTO on the five pillars a trustworthy AI system has to meet: grounded, explainable, reproducible, verified, and governed.
When the Foundation Is Already Right
The gap is rarely the model. It’s the data, the clinical context, and the governance underneath. See how Alnylam moved a week-long analysis to minutes.
Watch an Analysis From Question to Code
A Komodo expert runs a real analysis while you watch every tool call, query, and data filter. Stop at any step and ask why Marmot chose it. Bring your own therapeutic area, or use ours.
Healthcare Data and Analytics Platform FAQs
What Is a Healthcare Data Platform?
A healthcare data platform links claims, clinical, lab, and provider data into one analysis-ready dataset, then applies analytics or AI against it. A vendor delivers healthcare data products as files your team still has to join, clean, and validate. A platform does that first, so the first question gets asked on day one.
What Is the Difference Between a Healthcare Data Platform and Healthcare Analytics Software?
Healthcare analytics software gives your team tools to analyze data it already has. A healthcare analytics platform brings the data and the analytics together, with the linking already done. Three questions separate them: who refreshes the data, how records are linked, and whether methods can be reproduced.
What Data Sources Does a Healthcare Analytics Platform Need?
Linkage matters more than source count. A full patient journey needs medical and pharmacy claims, electronic health records, lab results, and provider affiliation data. Sources that cannot be tied to the same de-identified patient produce parallel views, not one journey. Komodo links 60+ sources at the patient level.
How Is Healthcare-Native AI Different From Frontier AI Models?
Frontier models learn from broad internet text and reason about healthcare from general knowledge. Healthcare-native AI is built on a specific clinical dataset and tested on real healthcare analytical tasks and clinical codesets, so it handles coding systems, cohort logic, and the methods that matter in the nuance of healthcare analytics.