Smarter Risk Stratification. Built to Work in Today’s
AI World

If you’re struggling to combine your claims, demographic, SDoH, and clinical data to elevate your predictive models and enable a more holistic risk assessment, we can help.

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How We Help

Turn member data into better care decisions without over engineering it

At X by 2, we partner with health plans to design, build, and operationalize integrated analytics and AI-based risk stratification models that align with your goals and your capacity. Our team brings the technical depth and the healthcare experience to identify the most impactful opportunities to implement AI.

If You Have Limited Data Science Capacity.

We help you start strong and scale with confidence

We act as a force multiplier for your internal team, bringing the tools, frameworks, and practical experience to help you launch quickly using the data you already have.

In a recent project, X by 2 developed a predictive model that delivered immediate results to build trust, then expanded it across disease areas with ongoing refinement to scale confidently.

We also help leadership teams evaluate the best-fit AI and ML use cases based on available data, internal workflows, and measurable business goals.

 

Predictive modeling that brings together claims & clinical data Prioritize Best AI Use-Cases Modernize analytics tooling, workflows, & personnel

If Unifying Claims & Clinical Data Remains a Challenge

Analytics team in place, but your data is working in silos?

We help unify claims, clinical, and SDoH data to build predictive models that reflect the full member story and plug into care management workflows.

In one recent project, we found that data sets across EHR systems, claims repositories, and care management tools were disparate. We integrated these sources into a unified, secure environment, engineering pipelines to merge clinical, operational, and demographic data. By standardizing formats, resolving duplicates, and improving data quality upfront, we gave the analytics team a single source of truth they could use to train and refine predictive models—unlocking insights that were previously hidden in silos.

We also work with analytics and informatics leads to explore where AI & ML can drive impact in the short term while building toward longer-term maturity.

 

Data Pipeline modernization
Model & methodology Modernization Roadmap
Implementation support

Our Approach

Built for impact. Designed around your team

Focused on use cases that matter

We align models to real-world goals like reducing admissions, closing care gaps, improving Stars/HEDIS performance, or identifying rising-risk members.

We start with your existing systems, data, and models

Ehancing precision and impact—so you see measurable results quickly, without costly platform overhauls.

Collaborative by default

Mitch Quinn, our healthcare AI Architect, works side by side with analytics, clinical, and population health leaders to build solutions that make sense and can be adopted quickly.

Common Use Cases

Where Risk Stratification Delivers Early Wins

Rising-risk member identification for early outreach

Predicting inpatient admissions or avoidable ED visits

Pediatric population segmentation

Behavioral health risk modeling

Prioritizing caseloads for limited care teams

Enhancing Stars, HEDIS, and quality performance

Supporting Medicaid and Medicare VBC programs

Surfacing SDoH-driven risk indicators

VP of Population Health

Managing rising-risk cohorts, showing ROI

Who We Work With

We work across clinical, operational, and data teams. From VPs of Population Health to Directors of Clinical Informatics, we partner with leaders responsible for both insight and execution.

Director of Strategy or Innovation

Piloting AI and ML with business value

Director of Care Management

Prioritizing daily caseloads

Chief Medical Officer

Reducing admissions, improving quality

VP of Quality

Boosting HEDIS, Stars, and quality outcomes

Chief Data and Analytics Officer

Scaling predictive infrastructure

Director of Health Equity

Flagging high-risk, underserved groups

Director of Population Health Analytics

Segmentation and visibility

VP of Clinical Transformation

Embedding insights into clinical ops

VP of Medicaid and Medicare

Performance in government programs

Why X by 2

We’re a technology consulting firm at the intersection of data, AI, and healthcare

 

Our work spans predictive modeling, data strategy, and system architecture. We understand the operational realities payers face and deliver solutions that balance early impact with long-term scalability.

Mitch Quinn

Director of AI/ML

Mitch Quinn, our healthcare AI Architect, helps payers identify their most impactful AI and ML opportunities and build a risk stratification roadmap that aligns with internal goals and capabilities.

Deep-learning risk modeling

Led CarePath at BCBSNC, a real-time 30-day readmission predictor used by care teams.

Care management impact

Helped raise care management engagement from 12% to 57% through timely, targeted outreach.

Recognized excellence

2nd place, 2021 Healthcare Innovation Innovator Awards for predictive analytics work.

Leadership & delivery

Former AI Applied Research Scientist at BCBSNC; now Director of AI & ML at X by 2.

Ready to Build Smarter Risk Models?

Whether you’re building from scratch or want to improve what you already have, we can help. Let’s explore what practical, predictive AI looks like for your plan.

Talk to Mitch Quinn