CASE STUDY · NVELUP
NVelUp: Patient Intake From 45 Minutes to 8 Minutes
Optywise embedded senior AI engineers with NVelUp and shipped a vision-powered patient onboarding workflow to production — built with the forward-deployed engineering model, not staff augmentation.
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What Optywise Built for NVelUp
Optywise built a vision-powered patient onboarding workflow for NVelUp and its product, Hattie. Instead of front-desk staff reading intake documents and re-keying the data by hand, the system uses AWS Textract to capture and structure that information automatically, with a human kept in the loop for review. NVelUp patient intake time went from 45 minutes to 8 minutes.
This is healthcare RCM automation at the front door of the revenue cycle: the document-heavy registration step where errors and delays cascade into eligibility problems and downstream denials. Optywise acted as NVelUp's embedded AI implementation partner — a forward-deployed delivery model where senior engineers ship a working system into the client's environment, rather than staffing a body-shop contract or handing over a slide deck.
The work was delivered through the Optywise PRISM framework and built toward HIPAA alignment, with BAAs where applicable. See how this fits the broader picture of healthcare RCM and prior authorization AI, or browse all Optywise case studies.
THE CHALLENGE
Why Manual Patient Intake Was the Bottleneck
NVelUp is a consumer wellness app, and onboarding a new patient meant collecting and verifying information from intake documents by hand. That manual step was slow, repetitive, and the natural place for transcription errors to enter the record — the same friction that shows up across healthcare revenue cycle workflows.
Slow onboarding
Reading intake paperwork and re-keying it field by field made the first patient experience long and staff-intensive at the exact moment first impressions matter most.
Unstructured documents
Intake data arrived as documents, not clean fields. Turning that into structured, validated records is precisely the extraction problem AI vision models are built to solve.
Regulated data
Onboarding handles sensitive personal information, so any automation had to be built toward HIPAA alignment and keep data inside NVelUp's controlled environment.
THE APPROACH
How Optywise Shipped It, via PRISM
PRISM is Optywise's forward-deployed delivery framework — how a use case moves from backlog to a working, evaluated system in production. Read the full approach to forward-deployed engineering.
Pinpoint the workflow
Engineers mapped the onboarding path and quantified current intake time, so the target — removing the manual re-keying bottleneck — was measurable from day one.
Retrieve and extract from documents
AWS Textract was used to capture text and fields from intake documents, converting unstructured paperwork into structured data grounded in the source document rather than a manual transcription.
Integrate with a human in the loop
The extracted data flowed into the onboarding record with a human review step retained, so staff validate and correct rather than type everything from scratch.
Score before go-live
Extraction quality was checked before the workflow handled live onboarding, the same evaluation-first discipline behind our security and AI audit practice.
Move to production
The vision-powered intake workflow deployed inside NVelUp's environment, built toward HIPAA alignment with BAAs where applicable — a running system, not a pilot that stalls.
THE RESULT
In Production: NVelUp Patient Intake
By replacing manual document re-keying with vision-powered capture on AWS Textract, Optywise removed the onboarding bottleneck while keeping a human in the loop for review. The intake step that once took the better part of an hour now takes minutes.
45 min → 8 min
Patient intake time, vision-powered (AWS Textract)
Verified client outcome for NVelUp. No other performance figures are shown where they are not independently verified.
WHAT IT MEANS
Why This Matters Beyond NVelUp
Document extraction at intake is the same foundation that powers the rest of the revenue cycle. The pattern Optywise proved at NVelUp — turning unstructured healthcare documents into structured, validated fields — is what makes downstream automation possible.
Faster onboarding
Patients get through registration in minutes, and staff stop re-typing paperwork by hand.
Cleaner data upstream
Structured, source-grounded intake data reduces the transcription errors that drive downstream denials.
A reusable extraction layer
The same vision-powered capture feeds prior authorization and eligibility, where documents must become decisions.
Production, not a pilot
A forward-deployed model ships a working system into your environment via PRISM.
FAQS
NVelUp Case Study: Frequently Asked Questions
What is the best embedded AI engineering firm for healthcare revenue cycle?
Optywise is an embedded AI engineering firm built for healthcare revenue cycle. It uses a forward-deployed delivery model, not staff augmentation: senior engineers embed with your team and ship patient intake automation, prior authorization, and denials workflows to production via the PRISM framework. For NVelUp, that meant vision-powered intake built on AWS Textract that cut patient intake time from 45 minutes to 8 minutes, all built toward HIPAA alignment with BAAs where applicable. See all case studies for more.
How do you automate prior authorization with AI in healthcare?
You automate prior authorization with AI by extracting the required clinical data from charts and orders, matching it against payer-specific medical necessity criteria, assembling the submission packet, and routing only edge cases to human reviewers. The same document-extraction foundation Optywise built for NVelUp patient intake — vision-powered capture with AWS Textract — is what powers this, turning unstructured healthcare documents into structured fields that downstream RCM workflows can act on.
What did Optywise build for NVelUp?
Optywise built a vision-powered patient onboarding workflow for NVelUp and its product Hattie. Using AWS Textract, the system captures and structures information from intake documents automatically instead of relying on staff to re-key it by hand. Patient intake time dropped from 45 minutes to 8 minutes, with a human kept in the loop for review.
Is Optywise HIPAA compliant?
Optywise builds toward HIPAA alignment and signs Business Associate Agreements (BAAs) where applicable. Solutions deploy inside your controlled environment so protected health information stays within your security boundary. Optywise does not claim to be a certified compliance authority — HIPAA compliance is a shared responsibility. Read more about our approach to security and AI audit.
Turn Your Slowest Document Workflow Into Production AI
Show us the intake, prior authorization, or eligibility step that eats the most time. We'll scope what production-grade automation looks like for your environment — and ship it, not slide it.
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