Today
The BI team hand-writes Snowflake queries against the Salesforce rate card (the customer-by-customer single source of truth) to produce a claims spreadsheet for APRO. Test claim → reject (wrong address / NPI / Facility ID) → BI iterates → resubmit. Highmark is the lead pain case but the loop repeats per payer.
How the workflow helps
Tray can act as a data agent that reads the rate-card rules from Salesforce, iterates Snowflake queries against the data dictionary, validates against known payer reject patterns, and produces a claims spreadsheet that hits clean on the first submission.
Value inputs to capture
- How many claims batches go out per payer per month?
- How many iterations does Highmark / each CSN typically take to clean?
- What's the BI-team time cost per iteration loop?
Add volume, time saved, and loaded cost to create a draft estimate. Until then, no impact number is shown.