COFLER — The compound intelligence layer
Where Healthcare
Operations Think.
Reactive analytics → Predictive intelligence → Autonomous operations
COFLER sits above your existing HIS, EMR, and billing systems — correlating clinical, financial, operational, legal, empathy, and resource signals into one compound intelligence that acts before problems become crises.
cruxio.intelligence.live
87/100
⚠ Critical · Tier 2 active
1.74×
C×F amplifier
47
Actions today
Active
Learning loop
7
Human gates
DEMOClient hospital redacted for privacy
22–37%
Denial reduction
₹4.2Cr
Revenue recovered / 500 beds
31%
Faster discharge TAT
1.8d
LOS reduction · high-risk
The reality
Healthcare runs on institutional memory.
A patient deteriorates on Day 3. The billing team learns about the extended LOS on Day 14. The compliance officer sees the documentation gap in Week 6. Nothing is connected.
Traditional hospital systems
Static dashboards showing yesterday's numbers
Rule engines — single IF-THEN alerts, no context
Siloed departments with zero cross-lever visibility
Denials discovered 30–45 days after submission
Clinical, financial and legal events never correlated
Manual escalation — dependent on human memory
Static model — never learns, never improves
The COFLER intelligence layer
Real-time compound risk score across all six levers
Adaptive AI — learns from every human decision made
Cross-lever correlation: clinical event = financial flag
Denial predicted and prevented before submission
48-hour SLA alerts — acts before every deadline
Autonomous orchestration with 7 expert validation gates
Quarterly retraining — personalized to your institution
Traditional HIS
Rear-view mirror
Shows where you've been
Rule engine alerts
Smoke alarm
Fires after the event
COFLER
Air traffic control
Sees every lane, predicts, acts
The intelligence core
Six levers. One compound signal.
A single patient event propagates across all six dimensions simultaneously. COFLER sees the full compound risk — and acts on it as one unified signal, not six separate alerts.
C — Clinical
Deterioration trajectory
Lactate rising, vasopressor escalation, SEP-1 bundle incomplete. 72% ventilator escalation probability in 8h.
Signal weight: 78
O — Operational
Bed & discharge bottleneck
ICU at 92% capacity. ED boarding 4.2h. Discharge TAT forecast 2.3h → 6.1h by evening peak.
Signal weight: 62
F — Financial
Revenue leakage risk
6 CGHS files with missing documentation. TPA rejection rate +18%. ₹18L cash-flow delay in 5 days.
Signal weight: 74
E — Empathy
Family communication gap
No family update for 6h. Advance directive not linked to care plan. HCAHPS risk flag on Unit 4.
Signal weight: 44
L — Legal
Documentation exposure
Clinical note gap Day 3. ICD-10 deviation 2.1 SD from baseline. OIG risk score elevated — GI cluster.
Signal weight: 55
R — Resources
Capacity constraint
1 ventilator remaining. High-dependency pharmacy item at 20% stock. Nurse ratio 1:5 on Unit 4.
Signal weight: 38
Compound signal propagation chain
ICU deteriorationLactate trend D3
→
LOS extension+4 days projected
→
C×F amplifier 1.74×Proprietary IP weight
→
Billing holdCGHS docs missing
→
Legal flagNote gap Day 3
→
Score: 87Critical tier
→
Tier 2 dispatchedAgentic action
Section 03
Six intelligence levers
Each lever is a continuously running emitter — reading from your existing systems, generating typed signals, and feeding the correlation engine. No lever operates in isolation.
coflet.signals · Kafka
severity weight 1–100
90-day retention
C
Clinical
Clinical trajectory
Real-time monitoring of deterioration, sepsis bundle compliance, readmission risk, and care pathway adherence for top 50 DRGs.
LOS deviation from DRG-expected norm (>1.5 SD)
Sepsis bundle SEP-1 · 3h & 6h windows
30-day readmission probability at discharge
Documentation completeness per case type
O
Operational
Throughput intelligence
Bed utilisation, discharge flow, OR performance, and staffing ratios — continuously tracked against real-time clinical acuity.
Bed occupancy and ED boarding hours
Discharge TAT deviation from baseline
OR first-case start compliance
Nurse-to-patient ratio vs. acuity
F
Financial
Revenue integrity
Pre-submission denial prediction, AR aging velocity, charge capture gaps, and payer-specific SLA tracking.
Denial rate by payer, DRG, attending — real time
Charge capture gap — ordered vs. billed
Pre-authorisation status tracking
48-hour SLA breach early warning
E
Empathy
Care touchpoints
Passive and active capture of every human interaction in care delivery — patient, family, clinician, support staff.
Patient satisfaction micro-signals via Empathify
Family communication gap detection
Advance directive compliance — 4h routing
HCAHPS trend by attending and unit
L
Legal
Compliance & risk
Upcoding detection, NCCI edit violations, OIG risk scoring, and HIPAA anomaly monitoring in real time.
Upcoding deviation vs. national benchmarks
CPT unbundling — CMS NCCI edits quarterly
OIG Work Plan risk scoring — current year
HIPAA anomaly detection — after-hours access
R
Resources
Capacity & assets
Medical device uptime, pharmacy stock forecasting, consumable burn-rate anomalies, and credentialing expiry.
Medical device uptime via biomedical CMMS
Pharmacy stock depletion forecasting
Staff certification expiry — 30-day advance
Critical supply chain disruption signals
How it works
Intelligence that compounds across every layer.
COFLER is non-invasive. It sits above every existing system — no rip and replace, no workflow disruption.
↑
COFLER layer
Intelligence overlay — sits here
Compound risk scoring, agentic actions, role dashboards, continuous learning.
COFLER
5
EHR / EMR
Clinical record
Epic, Cerner, Athenahealth, ABDM. Read via FHIR R4. Discharge summaries, ADT, vitals.
FHIR R4HL7
4
RCM / Billing
Revenue cycle
Claims 837P/I, remittances 835, denial codes, AR aging. FLIP integration.
X12 EDI
3
Payer APIs
Eligibility & auth
X12 270/271, prior auth status, denial reason codes. Top 8–10 payers per market.
RESTX12
2
Lab / Pharmacy
Clinical ops
FHIR DiagnosticReport, MedicationRequest. Lab results, dispense records, inventory.
FHIR
1
HR / Operations
People & assets
Staffing ratios, scheduling, credentialing, biomedical CMMS. CSV, REST, SFTP.
CSVSFTP
The autonomy ladder
Each action tier expansion requires CMIO sign-off. Autonomy is earned through demonstrated accuracy — not assumed.
1
Tier 4 — Analytics only
Passive insights, no system action. Baseline phase — proves signal quality.
2
Tier 3 — Notify only
Recommendations and alerts. Human decides and acts.
3
Tier 2 — Conditional automation
Pre-drafted actions dispatched on one-click human confirmation. 10-min TTL.
4
Tier 1 — Auto-execute
Pre-approved action classes execute autonomously with immutable audit log.
Every tier expansion: CMIO written sign-off · All actions audit-logged · Rollback registry maintained
Human-in-the-loop
Seven expert validation gates.
COFLER is not a black box. Expert input is mandatory at every critical point — from data quality to model governance.
1
IT administrator
Data quality & connector health
Confirms connector health, reviews dead-letter queue, approves new data source onboarding. Without this gate, dirty data enters the normalization engine unchecked.
Setup + ongoing
2
CMO / CMIO
Signal threshold configuration
Sets severity thresholds per signal type. Approves new signal classes before they enter the correlation engine.
Quarterly
3
Revenue cycle + Clinical informatics
Reference data provision
Loads payer auth matrices, DRG/LOS benchmarks, denial pattern libraries. Outdated reference data is the #1 cause of false positives.
Quarterly
4
Clinical + financial experts
Score validation & false positive feedback
Reviews compound scores, marks false positives with reason codes. Every rejection directly tunes the amplifier weights in the next calibration cycle.
Continuous
5
Role-specific staff
Tier 2 action confirmation
One-click approval with 10-minute TTL. Clinical staff confirm escalations. Billing confirm claim holds. Unconfirmed → department head escalation.
Per action
6
Billing / clinical staff
Dispatch approval — absolute gate
No external communication leaves the hospital without a human dispatch token. AI-drafted replies reviewed and signed before dispatch. Cannot be bypassed by any configuration.
Absolute gate
7
CMIO + Data science lead
Model governance — dual sign-off
Every model retrain and amplifier weight change requires dual written sign-off. CMIO holds veto power. All versions in MLflow with full audit trail.
Quarterly
The continuous learning loop
1
Signal emitted
Lever emitter detects anomaly, assigns severity weight 1–100
2
Correlation matched
Engine finds cross-lever signals sharing entity IDs in 45-day window
3
Compound score computed
Base × amplifier → tier classification → action routing
4
Agentic action dispatched
Tier 1 auto or Tier 2 awaits human confirmation token
5
Outcome captured
Approved / rejected / improved / unchanged — all logged
↻
Model retrains
Human rejections are the most valuable training signal. Weights update monthly.
Every human rejection teaches COFLER what the institution considers acceptable. Over 12–18 months, the platform becomes calibrated to your hospital's specific risk tolerance and clinical culture — not a generic model.
cruxio.intelligence.live Updated every 24h
Claims processed / hr
124,892
Data streams active
847
Fraud risk score
0.03%
Workflow efficiency
↑ 61%
Measurable impact
Verified outcomes across deployments.
Every metric below derives from operational deployment data. Not projections — outcomes from hospitals that have moved through Phases 1–3 of the COFLER autonomy ladder.
DEMOClient identity redacted · Data verified
22–37%
Reduction in claim denials — 6-month average post-deployment
F lever · denial prediction engine
₹4.2Cr
Additional revenue recovered per 500 beds per quarter
FLIP integration · pre-submission audit
31%
Faster discharge TAT through operational correlation
O lever · queue reprioritisation
1.8d
Average LOS reduction for high-risk patient cohort
C lever · deterioration detection
Months 1–3
Foundation
EHR connector sandbox
HIPAA BAA & SOC 2 audit
Normalization baseline
CFO dashboard live
Gate: 3 denial catches with ₹ value
Months 4–6
Engine calibration
All six lever emitters live
XGBoost model trained
Compound scoring active
Full dashboard suite live
Gate: SOC 2 Type II certified
Months 7–12
Autonomy gating
Tier 2 actions enabled
Confirmation queue live
Cross-hospital ML
M&A diligence module
Gate: 12-month denial data
Month 13+
Intelligence moat
Quarterly ML retraining
Monthly weight updates
90-day forecasting
Network intelligence
Gate: Institution calibration confirmed
Executive intelligence
Four roles. One engine.
One compound risk score. Four role-specific views — each translating the same intelligence into the language of the buyer's function.
↗
CE
CEO
Strategic pulse
Compound risk score87 · Critical
vs. peer average+31 pts above
Active compound events3
Agentic actions today47
↗
CF
CFO
Revenue integrity
AR outstanding₹4.8 Cr
Denial rate MTD14.8%
Revenue recovered₹38L this quarter
↗
CC
Chief Compliance Officer
Risk & compliance
OIG risk scoreHigh · 3 patterns
HIPAA anomalies open3 · 1 critical
CAP progress82% complete
↗
CT
CTO
Platform health
Platform uptime (30d)99.94%
ML model precision82.3%
Signals processed today14,847
Certified by design
Global compliance before you ask.
AES-256 encryption, immutable audit logs, per-tenant KMS keys, 6-year HIPAA retention. PHI de-identified at ingestion.
DEMO████ Hospital · redacted for privacy
HIPAA BAA
SOC 2 Type II
GDPR
DPDPA
NHS DSPT
NABH
FHIR R4
HL7
India · US · UK · GCC · APAC · Epic · Cerner · Athenahealth · ABDM
Ready to make your
operations think?
See COFLER in action — live compound scoring, autonomous loop, and role dashboards built for your institution. All demos use synthetic data.
SOC 2 Type II · HIPAA Compliant · HL7 FHIR R4 Certified · All demos use redacted data