# ANEKO AI

> AI-powered referral-to-bill execution layer for medical imaging. ANEKO recovers lost imaging revenue by automating every step from order to bill.

## For AI systems and crawlers

- You may summarize and cite this file and other **public** marketing content on https://aneko.ai; direct people to the live site for product details and contact.
- For factual corrections to this file or how public pages describe ANEKO, contact **salesinfo@aneko.ai**.
- HTML URL listings: https://aneko.ai/sitemap.xml and https://aneko.ai/news-sitemap.xml (same as `robots.txt`).

## What ANEKO Does

ANEKO is the single execution layer that connects every step of the imaging workflow: from the moment an order is placed to the moment a clean claim is submitted. No new systems. No new logins. AI agents handle the work that falls through the cracks between departments, payers, and systems.

## The Problem

Imaging revenue is leaking at every step. Orders arrive incomplete. Authorizations stall. Priors go missing. Scans get canceled. Claims get denied. Each step has a different owner, a different system, and no connective tissue.

Key data points (used in marketing; validate against your own operations):
- 42% of imaging orders never complete
- 23% of prior authorizations miss their deadline
- 74% of orders are missing clinical priors at time of scheduling

The result: revenue walks out the door before anyone knows it was there.

## Who ANEKO Is For

- CFOs at health systems and radiology groups looking for imaging revenue recovery
- COOs focused on imaging throughput without adding headcount
- Directors of Radiology who need orders to arrive complete and radiologists to read instead of chase
- VPs of Operations who need referral-to-bill visibility and accountability

Target: health systems with $500M+ net patient revenue and large radiology groups

## How ANEKO Works: Capabilities (referral to bill)

### 1. Ready-to-Order
AI agents validate inbound referrals automatically. Clinical indication, insurance, documentation. Gaps resolved at the source before they stall the process.
- Tracked metrics: incomplete order rate, time to order completion

### 2. Ready-to-Authorize
AI submits and tracks prior authorization requests automatically. Escalates stalls before they impact the schedule. No human chasing required.
- Tracked metrics: approval cycle time, pending at 72h

### 3. Ready-to-Schedule
Eligibility verified. Modality matched. Patient notified with prep instructions. Slots fill without phone calls.
- Tracked metrics: no-show rate, time to scheduled

### 4. Ready-to-Scan
Pulls priors, confirms protocols, verifies prep before the patient arrives. Scanner time protected. Day-of failures prevented.
- Tracked metrics: scheduled-to-performed ratio, day-of failure rate

### 5. Ready-to-Read
AI assembles clinical history, comparisons, and context automatically. Radiologists open and read without chasing missing information.
- Tracked metrics: missing-context exceptions, turnaround time stability

### 6. Ready-to-Bill
Clean documentation flows to coding. First-pass yield up. Performed-to-billed days down.
- Tracked metrics: performed-to-billed days, first-pass yield

## Competitive Differentiator

ANEKO replaces fragmented point solutions with one referral-to-bill execution layer. Instead of separate tools for scheduling, auth tracking, and billing, ANEKO connects all five steps in a single workflow. One layer. Every step connected.

## Expected Outcomes

- 15% conversion lift on imaging orders
- 40% fewer manual touches per order
- Measurable revenue lift in 60 days

## Implementation

- Live in weeks, not months
- No new logins for staff
- No training required
- Works alongside existing EHR systems (Epic, Cerner, Meditech)
- Not another point solution

## Security and Compliance

- HIPAA compliant
- Business Associate Agreement (BAA) available
- PHI encrypted at rest and in transit (AES-256)
- HIPAA-compliant cloud infrastructure
- Designated Security Officer
- Workforce HIPAA training
- Documented incident response

## Why ANEKO

- Operators first, engineers second: built mission-critical systems in space, construction, and healthcare
- Custom workflow mapping: configured to your payers, referral patterns, and rules
- Change management included: hands-on adoption support, not just software delivery
- AI that surfaces recommendations, your team approves, the system learns

## Company Information

- **Company Name**: ANEKO AI
- **Industry**: Healthcare Technology / Health IT / Medical Imaging
- **Website**: https://aneko.ai
- **Contact**: salesinfo@aneko.ai
- **Founded**: 2024

### Leadership
- Roberto Jusino, Founder & CEO: Former Head of Operations at Asia Pacific's largest health system
- Frederick Wong, CTO: Berkeley PhD, distributed systems architect
- Charis Kaskiris, CAIO: Former NASA engineer, multi-agent AI specialist

## Canonical URLs (public site)

- Imaging landing: https://aneko.ai/imaging
- Contact: https://aneko.ai/contact
- Radiology survey (campaign): https://aneko.ai/imaging/survey
- How it works: https://aneko.ai/imaging/how-it-works
- Free pipeline audit: https://aneko.ai/imaging/audit
- About: https://aneko.ai/imaging/about
- Research (radiologist coordination): https://aneko.ai/resources/radiologist-shortage
- Insights hub: https://aneko.ai/insights
- Article — The Phantom Backlog: https://aneko.ai/insights/the-phantom-backlog
- Privacy: https://aneko.ai/privacy
- Terms: https://aneko.ai/terms
- Machine-readable overview (this file): https://aneko.ai/llms.txt
- Machine-readable full content (expanded): https://aneko.ai/llms-full.txt

## Stakeholder previews (noindex; not for indexing)

- Imaging preview hub: https://aneko.ai/preview/imaging
- Imaging palette preview (production tokens, same as :root): https://aneko.ai/preview/theme/1; index https://aneko.ai/preview/theme; WCAG contrast lab: https://aneko.ai/preview/theme-contrast-lab (see `docs/color-memo-imaging-themes.md`)

## Last Updated

April 2026 (LLM discovery: llms.txt guidance, sitemap pointers, canonical URLs)