Deep healthcare and life sciences expertise applied to fragmented clinical, operational, and financial data, transformed into real-time intelligence across providers, pharma, and payers, without sending sensitive data outside your perimeter.
Accelerating cancer target discovery with a large-scale genomics analytics platform.
CHALLENGES
Critical signals surface in retrospective reports instead of in real time when decisions get made. Quality issues, cost overruns, and missed interventions compound until prevention becomes remediation.
Genomic, experimental, clinical, and safety data lives across systems that cannot reconcile. Target identification, trial recruitment, and adverse event detection take years longer than they should.
Clinical notes, imaging, research publications, and HCP engagement notes live in formats traditional infrastructure cannot use. The data exists; the ability to act on it does not.
HIPAA, GDPR, FDA, and CMS requirements constrain how data is accessed and modeled. Without governed domains and lineage, AI outputs cannot be reproduced, defended, or audited.
Capabilities
We unify clinical, operational, and financial data, govern it as a productized asset, and engineer the AI that turns fragmented data into real-time intelligence.
Prioritize use cases across operations, revenue cycle, patient journey, clinical trial work, and commercial
Design the regulation-aligned framework that operates AI defensibly across clinical and operational data
Unify clinical, operational, financial, and external data into a productized platform
Real-time visibility into operations, staffing, revenue cycle, patient journey, and the metrics leadership relies on
Deploy predictive models, conversational interfaces, document intelligence, and agentic workflows
Automate lineage, stewardship, and policy enforcement so AI outputs stay reproducible and defensible
Embed a dedicated team for continuous delivery across evolving data and AI priorities
Use Cases
Use Case
What it does
Use Case
What it does
Unified longitudinal patient view across encounters, claims, social determinants, and CMS resources, with care gap closure and behavioral segmentation.
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What it does
Causal inference and AI-driven recommendations for care manager outreach, intervention evaluation, and patient engagement at the right moment in the care journey.
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What it does
AI that extracts insights from clinical notes, research publications, regulatory filings, and operational documents.
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What it does
Genomic analytics, target identification, molecular modeling, and predictive biomarkers across drug discovery and R&D pipelines, with computational biology.
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What it does
Length-of-stay deviation surfaced daily, acuity-adjusted demand forecasting 8-12 hours ahead, and bed turnaround connected to clinical readiness signals.
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What it does
Real-time clinical documentation improvement (CDI) catches gaps while patients are in care, surfaces diagnoses that drive reimbursement (CC/MCC), and traces claim denials back to root causes.
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What it does
Match physicians to trial criteria, surface eligible patients from EHR data, and detect adverse events across the safety lifecycle.
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What it does
Catalog supply chain assets, deploy data marketplaces, and connect prescription, sales, and HCP engagement into a commercial intelligence layer.
FAQ
Compliance is engineered into every engagement. Our Governance Blueprint and Programs translate HIPAA, GDPR, FDA, and CMS frameworks into platform-level controls (role-based access, object-level security, lineage) from day one. AI activation never requires sensitive data to leave your environment.
Three core segments: providers and integrated delivery networks (including academic medical centers), pharmaceutical and life sciences companies, and healthcare payers. Use cases vary by segment, but the approach stays consistent across governed domains, AI activated inside the platform, and outcomes tied to KPIs.
Safe AI in healthcare comes down to domain authority and evidence-based methods. We elevate master domains (product, HCP, member, service line) into governed, versioned constructs AI executes against, with lineage that makes outputs reproducible and audit-ready. Predictive work uses evidence-based clinical scoring (LACE, MEWS, APACHE II, SOFA) plus ensemble methods for accuracy and explainability. AI runs inside your data perimeter; sensitive data never leaves your environment.
Most start with a Data & AI Strategy: focused discovery and prioritization across operational intelligence, revenue cycle, patient journey, clinical trials, drug discovery, and drug safety, followed by a phased roadmap. Delivery follows the strategy's top priorities.
Yes. We design around your environment (Epic, Cerner, Workday, SAP, Salesforce, Veeva, Medidata, IQVIA, claims feeds, and the hundreds of other applications healthcare and life sciences organizations run) and engineer on what you have. Our architecture aligns to HL7, FHIR, and OMOP standards. We bring deep expertise across leading cloud data platforms to accelerate delivery.
