How does the AI handle different payer rule sets?
Every payer has unique adjudication rules, fee schedules, and policy logic. We ingest your specific rule sets — across all lines of business — and the AI applies them consistently on every claim. When rules change (which they do constantly), we update the model. Your adjustors stop memorizing rule variations and start handling the cases that actually need clinical judgment.
Can you integrate with our existing claims platform?
Yes. We build on top of your current infrastructure — whether that's Facets, QNXT, HealthEdge, or a custom-built system. The AI layer sits between your existing systems, connecting data that doesn't flow today. Your IT team keeps managing infrastructure. We build the automation that makes it work harder.
How do we start — do we need to change our current systems?
No system changes required. We start with a 2-week AI Roadmap. Our engineers spend time inside your operation — watching your team work, mapping your claims flow, measuring your volumes. The output is a ranked list of workflows by ROI, with implementation timelines and expected savings. No commitment to build beyond the roadmap.
What about false positives in fraud detection?
Every fraud detection system generates false positives — the question is the ratio. Our models are tuned to minimize false positives while maximizing true catches. Every flagged case includes an evidence package with the specific patterns that triggered the alert. Your SIU reviews evidence, not hunches. False positive rates decrease over time as the model learns from your investigators' decisions.
What's the total cost for year 1?
Two options. Per Workflow: $25K-$75K per workflow, best for starting with one high-impact process. Dedicated Team: ~$22K/month for 2+ AI engineers embedded in your operation, building multiple workflows continuously. Most health insurers start with claims adjudication, prove the ROI, then move to a dedicated team. Every engagement starts with a free 30-minute assessment — no commitment.
How do we measure success?
We define success metrics with you before building anything. Typical metrics: claims processed per hour, straight-through processing rate, fraud detection rate, false positive ratio, credentialing cycle time, and cost per claim. We set up dashboards that show before/after in real-time. If the numbers don't improve within 90 days, we have a problem — and we fix it on our dime.