RISA Labs provides an AI‑driven platform that automates the end‑to‑end prior‑authorization workflow for oncology services, extracting data from EHRs, verifying eligibility, and generating medical‑necessity checklists. The system auto‑populates payer‑specific forms, submits requests via API, portal or e‑fax, and uses RPA bots and a dynamic rules engine to ensure compliance with payer guidelines and NCCN standards, reducing manual effort and claim denials.
Funding
$3.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
BBFounders
Product
Problem
Oncology clinics face fragmented prior‑authorization (PA) processes, with constantly changing payer guidelines and manual eligibility checks that consume clinician time and cause treatment delays. These inefficiencies increase administrative burden, elevate the risk of denied claims, and can adversely affect patient outcomes.
Solution
RISA Labs delivers an agentic AI platform that automates the end‑to‑end PA workflow for oncology services. A multi‑agent system reads EHR data, verifies patient eligibility, and cross‑references payer‑specific and NCCN guidelines to generate a medical‑necessity checklist. The platform auto‑populates payer‑specific forms, attaches required documentation, and submits requests via APIs, portal integrations, or e‑fax. A rules engine provides real‑time determination of whether a PA is required, while RPA bots handle repetitive portal interactions. The solution integrates with over 90 EHRs and supports HL7/FHIR, X12, CDA, and JSON standards, ensuring seamless data exchange and compliance with healthcare regulations.
Target Audience
The primary customers are oncology practice groups—including medical, surgical, radiation, and hematology oncology—and health‑system oncology departments that need to streamline PA submissions and reduce administrative overhead.
Features
- Multi‑agent AI architecture that orchestrates eligibility verification, medical‑necessity assessment, and form submission in a single workflow
- Dynamic rules engine that evaluates payer‑specific criteria and NCCN guidelines to produce a validated necessity checklist with attached evidence
- Auto‑population of payer‑specific PA forms and automated submission via API calls, web portals, or e‑fax, reducing manual entry errors
- RPA bots that automate repetitive tasks on payer portals, accelerating turnaround times for high‑volume oncology cases
- Integration layer that normalizes data from disparate EHRs and converts HL7®v2, CDA, X12, JSON, and DICOM formats into HL7®/FHIR® for downstream systems
- Large‑language‑model (LLM) processing of clinical notes to flag missing documentation and generate alerts that prevent denials
- Human‑expert oversight module that reviews complex cases and refines AI outputs, maintaining high accuracy and regulatory compliance