Pluto unifies siloed medical, insurance, and social determinants of health data from major US health systems to create a comprehensive patient view. The platform applies AI-driven clinical intelligence to identify care gaps, risks, and opportunities for improved health outcomes. It then facilitates closing these gaps by coordinating and delivering necessary resources, such as preventive screenings and at-home care, directly to patients.
Funding
Funding not disclosed
MSFounders
Product
Problem
Healthcare organizations struggle with fragmented medical, insurance, and social determinants of health data, leading to missed preventive screenings, delayed interventions, and inefficient care coordination across payors, providers, and life‑science partners.
Solution
Pluto aggregates structured and unstructured health information from roughly 90 % of U.S. health systems, including EMR records, claims, lab results, medication histories, and SDOH data, into a unified patient view without requiring patient recall. An AI‑driven clinical intelligence engine analyzes this consolidated record to surface care gaps, risk scores, and eligibility for clinical guidelines or research protocols within minutes. The platform then orchestrates delivery of appropriate resources—preventive screenings, vaccines, at‑home labs, and clinical‑trial pre‑screening—through automated workflows that can be embedded via API, white‑label solutions, or turnkey modules. Continuous event monitoring updates patient risk profiles as new diagnoses, insurance changes, or test results arrive, enabling proactive outreach and longitudinal follow‑up. All interactions are secured and compliant with SOC 2 Type II, ISO 27001, and FDA 21 CFR Part 11 standards, and are accessible through web dashboards and cross‑platform tools for clinicians, care coordinators, and patients.
Target Audience
Primary customers are health systems and provider networks seeking to close preventive care gaps, health insurers and payors aiming to improve population health metrics, and pharmaceutical or life‑science organizations that need real‑time patient identification for clinical trials.
Features
- Data unification engine that ingests and normalizes EMR, claims, lab, medication, and SDOH data from ~90 % of U.S. health providers, supporting both structured and free‑text sources.
- Ontology‑driven mapping using CPT, ICD‑10‑CM, SNOMED CT, and other clinical vocabularies to enable precise phenotype and eligibility definitions.
- AI/ML risk stratification models that generate real‑time care‑gap alerts, guideline‑based recommendations, and trial‑matching scores.
- Rules‑based and AI‑enhanced guideline alignment engine for automated matching to preventive protocols and research criteria.
- Event‑driven patient monitoring that triggers alerts on new diagnoses, insurance updates, or test results to sustain continuous care coordination.
- Flexible integration options: RESTful APIs, white‑label UI components, and turnkey deployment to fit existing clinical workflows.
- Cross‑platform engagement suite including patient web/mobile portals, clinician dashboards, and coordinator tools, with optional analog workflows for low‑tech users.
- Enterprise‑grade security and compliance stack (SOC 2 Type II, ISO 27001, FDA 21 CFR Part 11) with end‑to‑end encryption and role‑based access controls.