What's slipping through
42%42%
orders never complete
23%23%
authorizations slip
74%74%
priors never arrive
Based on analysis of imaging center order data across the groups we work with.
How it works
AI agents validate inbound referrals automatically. Clinical indication, insurance, documentation. Gaps resolved at the source before they stall.
Pending
12
Resolved
847
Accuracy
99.8%
MRI Lumbar Spine
Chronic low back pain
Blue Cross PPO
Not required (CPT 72148)
3 attachments verified
The difference
5 vendors. 5 logins. No shared data.
Revenue transformed
$4.8M
Revenue
96.2%
Completion
4.1
Days to Bill
94.8%
First-Pass
Implementation
Every vendor promises integration. You wait nine months. Revenue leaks the entire time.
ANEKO recovers revenue while the integration project is still in kickoff.
Your RIS stays. Your PACS stays. No new logins. No rip-and-replace.
Capabilities
Order to payment, nothing falls through the cracks
Fills gaps, chases approvals, and codes claims for you
Catches missing info before it becomes a rejection
Reminders, updates, and payment links they actually use
See what's working and what's stuck, right now
ROI
We baseline your current conversion, touch count, and cycle time. Then we show lift against your own numbers.
Free order intelligence audit
No integration required. Your order or claim data in any common format. Results in 7 days. HIPAA compliant.
Built for the people who run imaging
Revenue integrity and capital efficiency
Referral-to-completion
imaging conversion by site, payer, and modality
Performed-to-billed
lag days and first-pass claim yield on imaging
A finance-grade view of imaging revenue leakage, conversion, and claim quality tied to the same volume your operators see.
Throughput, authorization, and schedule execution
Prior auth cycle
submission to decision time for imaging procedures
Modality utilization
completed exams versus staffed scanner capacity
Imaging throughput KPIs that connect authorization, intake, and the schedule so empty slots show up as operational variance, not noise.
Clinical quality and worklist readiness
Worklist completeness
orders with auth, priors, and indication before read
Exam-to-report time
median hours from study complete to signed report
Visibility into whether studies are actually ready to read and where documentation and protocol friction slow the service line.
Architecture fit and speed to value
Time to production
first live workflows in weeks with bounded scope
Layer above core
RIS and PACS stay systems of record; execution on top
An AI-native execution layer you can roll out without waiting years on a brutal integration program or replacing imaging core systems.
Why ANEKO