Stop denials. Accelerate cash.
Stay audit-ready.
Perceive Now reconciles clinical, lab, coding, and billing narratives so claims go out cleaner, reimbursement cycles shorten, and audits don't become reconstruction projects.
Let us be direct.
Hospital Networks AI has a credibility problem.
Denials, appeals, and audits don't fail because teams don't work hard. They fail because proof is fragmented.
Denials instead of clean claims
Small mismatches across notes, labs, codes, and payer rules trigger preventable denials.
Appeals without evidence packaging
Recovery slows down when 'why this is true' is scattered across systems and inboxes.
Audit readiness as a quarterly fire drill
Audits go sideways when no one can trace decisions back to source without reconstruction.
Your teams aren't broken. Your stack is.
Disappointed with AI? You've come to the Right Place.
Insights
Denial rate:
Denials appear related to documentation gaps and coding mismatch.
Repeat mismatch:
Consider reviewing recurring CPT / ICD-10 combinations for potential issues.
Missing element driving denials:
Providers may need to improve medical necessity documentation.
Recovery priority queue (fastest cash):
Focus on high-value denials first for better cash acceleration.
Fact-Grid Intelligence
Denial rate:
9.8%
Repeat mismatch:
CPT 96372 + missing medical necessity detail
Missing element driving denials:
Modifier -25 + supporting note element
Recovery priority queue (fastest cash):
Top 42 claims = $310k potential
Core Capabilities
Day 1 ROI Guarantee
Not a roadmap. A requirement. Deploy one wedge workflow and measure delta fast.
Clean-Claim Orchestration
Reconcile clinical notes, labs, codes, and payer rules before submission.
Denial Recovery + Evidence Bundles
Root-cause denials, package proof, and resubmit with less rework.
Audit-Ready Lineage
When challenged, produce defensible trails instantly—no reconstruction sprint.
From Data Chaos to Decision Clarity
Stop fighting your infrastructure. Start leveraging it.
The Chaos
Before- Denials triggered by small inconsistencies across systems
- Manual review creates rework, delays, and slow cash collection
- Appeals take too long because evidence is scattered
- Audits go sideways when no one can trace "why this is true"
Hospitals lose money when notes, labs, codes, and payer rules don't align.
We don't replace your stack
We orchestrate it
The Clarity
After- One version of truth across systems
- Cleaner submissions + faster recovery
- Defensible trails by default
What changes when an OS replaces disconnected tools
Start where ROI shows up Fastest
High-ROI Workflows
Denial prevention
catch missing info + conflicts before submission
Charge capture validation
prevent missed revenue
Coding support
reduce CPT/ICD-10 + documentation mismatch loops
Denial recovery
root-cause + evidence bundle + corrected resubmission
Claims prioritization
bring cash in fastest (with evidence attached)
Audit readiness
traceability by default
Evidence retrieval
faster, defensible trails for reviewers
Validation documentation
automated QA artifacts ready on demand
Real-World Impact in 90 Days
The Challenge
Lotus Integrative Health was losing 18% of potential revenue to denials. Their team spent 3–4 weeks every quarter manually reconciling lab data, clinical notes, and billing codes.
The Solution
Perceive Now automatically cross-referenced clinical documentation with billing codes and payer requirements, flagging discrepancies before claims submission.
The Results
21%
Denial reduction
68%
Time saved
$1.2M
More revenue
4.3×
ROI at 6 months
ROI shows up differently by leader so we Quantify it by Function
CFO / Finance
- Cleaner revenue story
- Faster reporting cycles
- Measurable leakage reduction
VP Revenue Cycle
- Fewer preventable denials
- Faster resubmissions
- Less rework across coding
Clinical Ops/CDI
- Fewer reversals
- Faster closure of missing details
Compliance/Audit
- Fewer audit flags
- Faster evidence retrieval
Day 1 ROI is not a roadmap.It's a requirement.
Day 1
Baseline measured before first query (denials, rework, cycle time, audit effort)
First decision-ready output delivered from real data
Day 30
Measured delta vs baseline + executive readout
Expand from the first wedge into the next adjacent workflow
Day 60-90
Scale across sites/service lines
Standardize the playbook so gains compound quarter over quarter
