The rules are public.
The enforcement is private.
Every payer references the same clinical guidelines. How they enforce them varies by payer, by reviewer, by quarter. We structure that knowledge.
What a Precedent Object captures
01
Denial Classification — payer, code, LOC, diagnosis cluster
02
Evidence Sequence — what was submitted, in what order, what worked
03
Narrative Architecture — the argument structure that moved the reviewer
04
Traceability Chain — guideline clause → evidence → outcome (transparent proof chain)
05
Escalation Economics — cost to appeal, expected recovery, break-even
06
Outcome Label — overturned, upheld, partial, withdrawn
07
Governance Metadata — version, author, last validated, drift flags
Why it matters
Human-readable. Your billers can read, challenge, and update every layer.
Version-controlled. When enforcement shifts, the precedent updates that week.
Auditable. Every decision traces back to a guideline clause and evidence.
Yours. Not rented. Not vendor-controlled. Owned by your organization.
AI RCM / Manual billers
Metric
AI RCM
Manual
Drift detection
50–200+ examples
15–30+ failures
Update cycle
30–90 days
2–6 months
Cost per drift
$50K–$575K
~$115K
Governance
Vendor-controlled
Undocumented
Precedent Intelligence
~10 directed tests to validate a hypothesis
1–2 weeks to detect, test, & deploy update
$1K–$5K per drift event
You own it. Human-readable, editable, version-controlled.
AI drafts faster. We know what to say.
$20B spent in 2022 overturning wrongly denied claims. 90% of denied claims are preventable. AI models suffer “temporal quality degradation” as payer behavior drifts — precedent intelligence adapts in weeks, not quarters.
Your facility. Your payers. Your denial patterns.
We start with your data and show you exactly where precedent intelligence recovers revenue.
HIPAA
MHMDA
42 CFR Part 2