NANO Health Products
NANO BRAIN
The artificial intelligence underneath everything else.
Every product in the suite gets better the more the suite sees. NANO BRAIN is where that happens — a machine-learning layer trained on hundreds of millions of real claims, approvals and drug records, which then auto-processes transactions and explains its own decisions back to you.
What it is trained on
The corpus behind the model, as published in NANO's company profile.
240M+
Processed claims
300M+
Processed approvals
200M+
IDDK drugs data
30M+
Clinical pathways
15M+
Coding rules
900K+
Best practice
What it does with a transaction
Transactions are processed automatically, and the reasoning is not a black box.
Auto-processes the transaction
Each transaction is automatically resolved as approved or rejected.
Explains the outcome
Benefits and denial reasons are identified automatically, as part of that same auto-processing.
Identifies the deduction
Activity transaction, benefit deduction, specialty deduction and case-severity deduction.
Flags fraud, waste and abuse
Fraud, waste and abuse are surfaced as part of the same pass.
What it connects to
Through APIs, so the model serves the products rather than sitting beside them.
PBMIMSThird-party systems
Frequently asked questions
What is NANO BRAIN trained on?
- 240M+ processed claims, 300M+ processed approvals, 200M+ IDDK drugs-data records, 30M+ clinical pathways, 15M+ coding rules, and 900K+ best-practice records.
What does it actually do at run time?
- It auto-processes transactions to approved or rejected, and identifies the benefits and denial reasons behind that outcome automatically — along with activity, benefit, specialty and case-severity deductions.
Does it detect fraud, waste and abuse?
- Yes. Fraud, waste and abuse are identified as part of the same automatic processing pass.
How does it reach the other products?
- Through APIs, into PBM, IMS and third-party systems.
Is the decision explainable?
- The denial reason and the deduction type are produced with the decision, rather than left for someone to reconstruct afterwards.
Put it against your own transactions
We will run the model over a sample of your claims and show you what it approves, what it rejects, and the reason it gives for each.
Related products
Products in the suite that work alongside this one.