Understand disability.
Predict what comes next.
Decide with evidence.
Built on two careers inside SSA, we combine disability adjudication and law with economics, Bayesian modeling, spatial analysis, forecasting, and product design to turn fragmented data into actionable intelligence.
Built for disability firms, advocacy organizations, insurers, legal-technology teams, researchers, and investors.
opportunity
exposure
priority
See the market, the claim, the policy, and the portfolio together.
Disability organizations often answer each question in a different system. We connect them so leaders can see where demand, case value, operational performance, and policy risk reinforce—or contradict—one another.
Where is disability demand now—and where is it going?
- Identify high-opportunity markets
- Forecast demand by geography
- Explain demographic and economic drivers
Where should you invest for the strongest return?
- Optimize spend geographically
- Measure saturation and competition
- Lower avoidable acquisition cost
Which claims warrant attention, evidence, and investment?
- Surface evidence gaps
- Prioritize inventory
- Model outcome and value drivers
What happens when SSA changes a rule or process?
- Simulate operational impact
- Estimate exposure and opportunity
- Plan before implementation
What is happening across your entire caseload?
- Track performance and delay
- Find inventory risk
- Create management visibility
The “Disability Belt” is a signal—not an explanation.
A high disability rate can reflect age, health, work history, industry, poverty, access to care, program rules, or persistent regional structure. Raw county rankings do not tell leaders which forces are operating—or what to do next.
Our approach combines disability-domain judgment with spatial econometrics and Bayesian modeling to separate expected participation from unusual local patterns, identify statistically credible clusters, and connect those patterns to business and policy decisions.
From national disability data to organizational decisions
Intelligence infrastructure—not another consulting dependency.
We begin with a defined decision, prove value against real operating conditions, and convert what works into reusable modules, benchmarks, and executive visibility.
Portfolio Diagnostic
Connect intake, inventory, outcomes, processing time, and economics to locate the highest-value intervention.
- Performance baseline
- Risk and opportunity map
- Executive action priorities
Claim Intelligence Suite
Structured tools for the decisions that shape a claim from denial through evidence development, hearing, and review.
- Denial Decoder
- Evidence Gap Analyzer
- Hearing Prep and CDR tools
Disability Observatory
A geographic and policy-intelligence layer for understanding demand, testing scenarios, and anticipating change.
- County and regional signals
- Policy scenario modeling
- Forecasts and benchmark data
Public data provides the map. Domain expertise and advanced analytics provide the meaning.
The strongest intelligence is transparent about its sources, assumptions, uncertainty, and limits. Every output should be explainable to the people accountable for the decision.
- SSA data
- Census data
- Health data
- Economic data
- Geospatial data
- Authorized client data
- Disability policy analysis
- Bayesian statistics
- Spatial econometrics
- Forecasting
- Predictive modeling
- Product design
Explainable
Decision logic people can inspect and challenge
Legally grounded
Models designed around the actual adjudicatory framework
Built to scale
Repeatable products where repeated judgment creates value
Two SSA careers. Complementary disciplines. One shared decision model.
Both founders retired from the Social Security Administration. Linda brings adjudicative and legal judgment; Javier brings economic, statistical, and computational modeling. Together, they translate institutional knowledge into intelligence leaders can use.
Linda Cosme, Esq.
Linda retired from SSA after roles spanning Disability Quality, the Office of General Counsel, and the Appeals Council. Her earlier DDS experience and later claimant representation connect adjudication, litigation, policy, analytics, and product design.
- Appeals Council, OGC, and Disability Quality
- DDS examination and quality review
- 30,000+ claims adjudicated, reviewed, litigated, or analyzed
Javier Meseguer, PhD
Javier retired from SSA after serving as an economist in disability-program research. His published work applies Bayesian hierarchical models, spatial econometrics, forecasting, and computational methods to adjudicative outcomes, geographic variation, and program performance.
- SSA disability-program economics and research
- Bayesian, spatial, and forecasting methods
- Outcomes, geography, and program-performance modeling
Start with one consequential decision. Build the infrastructure around what works.
Early engagements are structured as design partnerships with a defined use case, evidence standard, and measurable business outcome—not open-ended advisory retainers.
Diagnose
Establish the portfolio, market, policy, or workflow baseline.
Prove
Test the model against real decisions and validate measurable value.
Standardize
Convert the validated method into a repeatable module or benchmark.
Scale
Deploy dashboards, products, and decision infrastructure across the organization.
What decision would become more valuable if you could see it clearly?
Tell us the business question, the data you have, the decision you need to make, and what a credible result would change.
Begin with four points
- Your organization and decision-maker
- The decision, risk, or opportunity
- The available data and timeframe
- The business outcome that matters