HealthLift runs the operational back office between care and payment: prior authorization, verification, billing, payment posting, reconciliation and more. Take one module or the whole cycle. We run it today for over 1.5 million covered lives, and we built it in pharmacy, healthcare's highest-volume service: U.S. pharmacies fill over 7 billion prescriptions a year, each adjudicated in real time at the counter.
Every stage has a checkpoint. When the system isn't confident, the item goes to a person, and it doesn't move on until they clear it.
We already stand behind over 1.5 million covered lives. The operation that serves them was built in pharmacy, where no other standalone healthcare service matches the transaction volume: claims adjudicate in real time at the counter, dollars per claim are small, and the next wave arrives every few minutes. That operation is the engine behind every service below.
For a payor, covered lives mean we already carry population responsibility. Eligibility, benefit rules and jurisdiction logic run live against your membership, not as a pilot.
For a pharmacy, covered lives mean the volume is already there. Those members walk into your store. Routing their claims to us is the difference between a paid claim and a turned-away patient.
Real-time by default. Pharmacy claims adjudicate at the counter, so problems get fixed while the patient is still there.
Thin margins demand good automation. At pharmacy volumes, manual handling doesn't pay. We had to build the automation and the human checkpoints properly.
Lower-volume services are easier. Prior authorization, medical billing and posting run at a fraction of pharmacy's pace.
Each module runs on its own, plugs into your systems, and connects to the others when you want the whole cycle. Every one is AI-assisted and human-decided. Pick a service to see which steps AI handles and where a person takes over.
Request, track and resolve authorizations without the fax-and-hold loop.
Every AI output carries a confidence score. Above the threshold it proceeds; below it, a person decides. Where we set that line is a business decision made with you, not a setting buried in the software. Drag the threshold to see the trade-off.
Illustrative model. Real thresholds are set per task and per client, and are moved only after a controlled batch shows the change is safe.
Posting a payment, submitting a clinical appeal, approving a refund: AI prepares these, and a person approves them.
Every extracted field links back to the page it came from, so reviewers and auditors see the source, not just the answer.
A new automated step goes live only after it matches historical human accuracy on a controlled batch. Until then, the existing process stays whole.
The log records who or what did each step, down to the person who entered and approved each posted dollar.
Callers reach trained staff. AI works in the background: routing, surfacing the right procedure, writing up the call.
We sit between the people who deliver care and the organizations that pay for it. Because we work both sides, we know what a clean claim looks like from each.
Most clients start with the module that hurts most, then connect more once the numbers show up.
One service, run in your systems, with your staff or in place of them. Clear volume, turnaround and accuracy targets.
Several modules joined end to end, so documents, verification, billing and posting share one record and one audit trail.
We bill and collect for you, with carefully aligned performance and risk reduction measures.
We'll show you how we'd run it: what AI would handle, where your team or ours would decide, and what we'd measure.
Talk to us