Work we have delivered.

Skilled-nursing reimbursement depends on the MDS assessment and the PDPM coding behind it. When documentation is thin or inconsistent, the facility finds out after submission. By then a fix means rework, resubmission, and money at risk.

Reviewers could only check a sample of records by hand, so most gaps surfaced late.

We built a system that reads each record before it is filed and flags missing or inconsistent documentation against MDS and PDPM requirements.

Each flag shows the passage that raised it. A reviewer on the operator's team makes every call.

Reviewers catch problems while they are still cheap to correct. Coverage no longer depends on how many records a person can read in a day.

Each division kept its own data in its own systems, with its own definitions. A question that crossed two divisions meant a manual reconciliation, and the answers rarely matched.

We built a unified data layer that pulls every division's sources into one place and reconciles them to shared definitions.

Questions that used to need a cross-division project now run against one model of the organization.

Leadership works from one set of numbers that every division agrees on. New questions start from data that already reconciles.

The firm's pipeline depended on signals spread across many sources. Analysts gathered them by hand, then sorted and scored each lead themselves.

We built a multi-agent system. Agents collect signals from each source, combine them into one record per lead, and classify each lead against the firm's criteria.

Analysts review the classified leads and decide which to pursue.

Analysts spend their time on judgment. Every lead arrives with the evidence behind its score.