Client Onboarding

Stop drowning in paperwork and manual checks.

We build custom AI systems that handle healthcare client onboarding from intake to compliance, tailored to your actual workflows.

See how it works
Healthcare client onboarding runs into strict HIPAA requirements, payer credentialing complexity, and constant staff turnover. Manual processes cause errors, slow down revenue cycles, and open up compliance gaps. Patients expect faster access to care, and admin overhead keeps growing -- so inefficient onboarding hits both margins and care delivery.
12 days
average patient onboarding cycle
Advisory Board, 2025
34%
of onboarding tasks are redundant data entry
KPMG Healthcare Ops, 2024
65%
reduction in onboarding time with AI automation
Deloitte Digital Health, 2025

What you're dealing with

Manually checking insurance eligibility across multiple payer portals, often with outdated or mismatched data
Chasing missing patient forms and signatures while staying within HIPAA communication rules
Coordinating between intake, clinical, and billing teams over email and spreadsheets, with constant version control problems
Re-entering the same client data into EHR, practice management, and billing systems one by one
Audit prep: pulling together compliant onboarding documentation from scattered sources at the last minute

How it works

We start by mapping your real onboarding process -- how intake actually happens, where data gets stuck, who handles exceptions. We run AI-driven interviews with your team to capture the unwritten rules and pain points. Then we design a custom system that automates data collection, validation, and routing based on your workflows. Our platform lets us build and deploy in weeks, not months. You get a single interface that pulls data from forms, EHRs, and payers, cross-checks for consistency, flags missing items, and syncs approved data to your systems. Compliance logging and audit trails happen automatically. This isn't off-the-shelf software -- it's built for your people, your systems, and your constraints.

Arc

Pulls and validates data from intake forms, insurance cards, and EHR systems -- catches errors and cuts manual entry

Wand

Routes work and handles exceptions based on your team's actual decision patterns, so processes keep moving without manual follow-ups

Before and after

Before
A new patient submits a form online. An intake coordinator prints it, manually checks insurance through a portal, re-keys data into the EHR, emails the clinical team for review, and follows up twice for missing information. The whole thing takes 3-5 days with multiple handoffs.
After
The patient submits a form. The custom system instantly validates insurance, cross-references existing records, routes incomplete items to the right team member via SMS or EHR task, and auto-populates systems once approved. Onboarding finishes in under 4 hours with a full audit trail.
  1. 1 AI validates insurance in real-time and flags discrepancies
  2. 2 System automatically requests missing documents via patient-preferred channel (text, email, portal)
  3. 3 Approved data syncs to EHR and billing systems without re-entry
  4. 4 Compliance log is generated automatically for each client
3 weeks
from kickoff to live deployment
For a regional clinic network handling 200+ new patients per month

Common questions

How do you handle HIPAA and data security?
Compliance is built into the system design. Data is encrypted end-to-end, access is role-based, and audit trails are automatic. We sign BAAs and follow your security protocols.
What if our EHR or practice management system changes?
The system is modular. Our internal tooling makes it straightforward to adapt to new systems or workflows -- we handle the updates, not you.
How long until we see a reduction in manual work?
Most teams see a 40-60% drop in manual onboarding tasks within the first two weeks of deployment. Full adoption typically takes 3-4 weeks with training and tuning.
Do we need to hire additional IT staff to manage this?
No. We build and maintain the system. Your team uses it -- we handle technical support, updates, and scaling.