SNAPPIA REVENUE CAPTURE ENGINE

What can it do?

Positioned in the mid-cycle claims processing engine, Snappia bridges EMR clinical records and standard claim forms with accurate, explainable automation.

Six ways Snappia improves the claims process

Autonomous coding

Problem: Manual coding and unconstrained language models create administrative drag, burnout, 10–15% initial denial rates, and higher collection costs.

What it does: Uses hierarchical reasoning, clinical LLM context, deterministic rules, CPT taxonomy, and validation to populate ICD-10-CM, CPT, and HCPCS codes directly onto claim forms.

Confidence scores for expert review

Problem: Black-box automation makes it hard for compliance and revenue teams to know when claims are safe to submit.

What it does: Outputs a percentage-based confidence level for each diagnosis and procedure code, routing claims for expert intervention when scores fall below a configured threshold such as 95%.

Trustable clinical rationale

Problem: Without explainability, AI-driven billing is difficult to audit and coding teams cannot verify why a code was assigned.

What it does: Produces natural-language reasoning that maps patient-report text to official CPT and ICD-10 descriptors and guidelines in the Show Logic view.

Human-in-the-loop workflow

What it does: Routes only lower-confidence or complex claims to expert reviewers, who can inspect the clinical note, AI rationale, and draft codes before submission.

Provider query for accuracy

What it does: Identifies when more specific codes may apply but documentation is incomplete, then prompts providers with structured, multiple-choice queries before finalizing billing codes.

Provider query for revenue capture

What it does: Detects plausible coding choices with meaningful reimbursement variance and issues a targeted provider query to capture full, compliant revenue entitlement.