Prior-authorization preparation
Collect the required chart information and supporting documents, identify missing fields, and prepare a review-ready authorization packet. Submission and clinical attestation remain with authorized staff.
Healthcare Operations
AI agents for the admin work your EHR doesn't do
We build controlled workflows around intake, prior authorization, billing, patient communication, and documentation, with clear staff review and exception handling.
Book an AI Ops AuditIntake and eligibility
Validate incoming forms, identify incomplete records, route eligibility checks, and create a clear exception queue before a visit.
Claim follow-up and appeals
Organize payer responses, deadlines, and supporting records so billing teams can review and act without rebuilding the history from multiple systems.
Patient communication
Trigger approved reminders and status messages with consent, opt-out handling, delivery tracking, and staff escalation for sensitive or failed conversations.
Billing RPA
Automate repetitive portal and data-entry steps while preserving record-level success, skipped, and failed outcomes for staff review.
Why not another scribe?
Many EHRs already include documentation assistance. Our focus is the operational work surrounding the chart: collecting complete intake, coordinating authorization material, following billing exceptions, routing communications, and moving validated data between systems.
Compliance is deployment-specific
Before production use, the project scope defines hosting, data retention, encryption, access control, audit logging, vendor agreements, user roles, and human review. A technology feature alone does not make an entire practice or workflow compliant.
Published Proof
SLPeace voice-to-note workflow
A voice-assisted documentation product for speech-language pathologists. Additional healthcare case studies will be published only after client disclosure and results are approved.
Map the workflow before choosing the model
Start with the handoffs, exceptions, staff roles, data boundaries, and measurable outcome. Then select the smallest system that can do the job safely.