Health insurance decisions backed by clause-level evidence, not assumptions.
Upload your policy schedules and hospital estimates. CLARIVO extracts verified facts, audits waiting periods and room rent traps, and simulates hypothetical out-of-pocket costs with mathematical precision.
Your policy caps standard room rent at ₹5,000/day. The hospital estimate specifies a Single Deluxe Room at ₹8,500/day.
How CLARIVO Eliminates Insurance Ambiguity
Standard AI tools summarize text with plausible-sounding hallucinations. CLARIVO uses a strict 4-step truth protocol anchored to verbatim clause citations.
Document Ingestion
Extracts structured text from policy schedules, wordings, hospital estimates, and bills with character-level offsets.
Epistemic Classification
Strictly classifies every data point: Verified Fact vs User-Stated vs System Inference vs Unknown.
Conflict Matrix
Cross-references hospital estimates against policy schedules to spot waiting period and sub-limit contradictions.
Decision Sandbox
Simulate what happens if you switch room categories or hospital tiers without altering your real policy record.
Engineered for Real Insurance Decision Friction
Health insurance disputes rarely happen because of bad intentions—they happen because policy conditions are buried in 40-page schedules.
1. Room Rent & Proportionate Deductions
Identifies 1% and 2% room sub-limits and calculates the exact cascading out-of-pocket impact if a higher room tier is chosen.
2. Pre-Existing Waiting Period Traps
Evaluates 24, 36, and 48-month waiting period clauses against your actual policy inception dates and medical diagnosis chronology.
3. Claim Preparation & Evidence Auditing
Constructs a checklist of mandatory hospital documents, doctor prescription notes, and diagnostic reports required before filing.
CLARIVO never pretends to guarantee insurer approval or offer formal legal advice. All conclusions provide provenance-grounded guidance.
Uploaded policy documents and case contexts are strictly isolated to your authenticated Supabase user profile.
Your medical estimates and private policy schedules are never used to train public foundation models.