Cut administrative time 80%, HIPAA-compliant throughout
A telehealth provider was processing patient intake and documentation by hand. We built an LLM-based intake and document-classification pipeline inside their existing HIPAA-compliant infrastructure, with a human-in-the-loop review step — cutting administrative time by 80%.
What we built
We apply machine learning and large language models where they solve a specific, measurable business problem: automating manual review work, forecasting demand, or giving your team an internal copilot grounded in your own data. Every model ships with a monitoring plan, not just a demo.
How we ran it
Assess
Audit data quality and the specific decision the model needs to support.
Architect
Model and pipeline architecture scoped to a measurable success metric, agreed up front.
Build
Iterative delivery with a working prototype early, refined against real data and real users.
Operate
Monitoring for drift and cost, with a review cadence to retrain or retire models.