We build private, auditable workflows that read referrals, intake forms, lab documents, prior authorization packets, and scheduling notes, then prepare tasks and handoffs for staff approval.
Forms, labs, notes, insurance cards, and clinical context arrive across fax, portals, email, and paper.
Staff spend too much time assembling packets, checking requirements, and chasing missing documentation.
PHI, insurance details, clinical notes, and scheduling context need careful handling, not public chatbot workflows.
Industry document automation research calls out patient records, insurance claims, referral forms, lab reports, and EOB documents as daily healthcare processing work.
Healthcare document automation research names CMS-1500 forms, free-text clinical notes, discharge summaries, lab reports, handwriting, scans, photos, and faxes as real-world complexity.
Healthcare extraction needs traceable outputs for HIPAA reviews, CMS audits, and payer oversight, so our workflows keep source evidence and approval history visible.
Extracts patient, provider, diagnosis, insurance, and requested-service details for review.
Assembles required fields and flags missing documents before submission stalls.
Reviews forms, labs, notes, and insurance details before the appointment workflow begins.
Prepares next-step tasks, appointment notes, and patient follow-up drafts.
Summarizes incoming records with source evidence for staff or clinician review.
Staff manually inspect every packet, chase missing fields, prepare prior auth details, and route scheduling tasks across systems.
The workflow extracts key facts, flags missing information, prepares handoffs, shows source evidence, and waits for human approval.
Private workflows can use hosted private-cloud inference, dedicated cloud or VPC deployment, or local/on-prem inference when PHI cannot leave your environment.
Avoid billing surprises with clear workflow-based packages. We do not penalize you for using more AI like other vendors.
Every result can carry source evidence, approval status, user actions, and write-back history so staff can review what happened before data moves.
We choose one referral, prior auth, or intake process with clear volume and staff pain.
We configure extraction, source evidence, human review, and PHI-safe deployment boundaries.
You see turnaround time, missing-info reduction, review quality, and the next workflow roadmap.
Founder, Performance AI Lab | Former Meta SuperIntelligence Lab
With 25 years in software engineering and enterprise infrastructure, I've built systems for some of the world's most demanding environments. I founded Performance AI Lab to bring private, auditable AI workflows that reduce manual work and preserve operating know-how to mid-market operators.
If your team is buried in documents, emails, approvals, spreadsheets, or software handoffs, we can help identify the first workflow worth automating.
Private AI workflows for the work that falls between your documents, apps, approvals, and operating knowledge.