Every Claim Takes Too Long to Settle
A claim that should take minutes sits in a queue for days. Eligibility checks, code validation, policy cross-referencing — all manual. At thousands of claims a week, that backlog costs money and erodes trust.
Stop Losing Rupees to Slow Claims and Fraud.
Automate adjudication, catch fraud before payment, and cut cost per claim — so your team handles complex cases, not paperwork.
Book a Claims AI DemoTrusted by startups and global leaders
What Is Actually Breaking Your Claims Operation
These problems are accepted as normal. They should not be. Each one compounds daily — in overhead, fraud losses, provider frustration, and eroded trust.
Fraud Is Outpacing Your Detection Tools
Duplicate claims and upcoding have been joined by billing rings, AI-generated documents, and synthetic identities. Rule-based systems catch only what they were programmed for — and miss the rest.
Denial Rates Are Too High for the Wrong Reasons
Legitimate denials happen. But preventable ones — wrong codes, missing documents, eligibility errors — drive rework, appeals, and provider frustration. Most organisations have too many and no clear way to reduce them.
Your Team Is Doing Work a Machine Should Do
Skilled analysts are keying data, cross-checking policies, chasing missing information, and routing simple claims that need no human judgment. That is an expensive way to use experienced people.
No Real-Time View of Fraud Risk
By the time a fraud pattern surfaces in a post-payment audit, the money is gone. Most organisations detect fraud after the fact, recover a fraction, and repeat the same cycle.
How the Platform Works — Stage by Stage
From intake to settlement, AI reduces manual work, improves accuracy, catches fraud, and surfaces the information your team needs at every stage.
What You See in the Claims Dashboard
Real-time visibility across the full claims operation — not a report you request, but a live view your entire team can act on the moment something needs attention.
Live Claims Pipeline
Every claim in the system, at every stage, in real time. Volume by status, by claim type, by provider, by region. No more asking the team for a status update — it is all visible the moment you need it. Straight-through processing rate and average settlement time tracked live.
Fraud Risk Heatmap
A visual view of fraud risk across your claims portfolio — by provider, by geography, by procedure type, by claim source. Where are the concentrations of suspicious activity? Which providers have moved up the risk ranking this month? Alerts surface before payment, not after.
Financial Leakage Report
Estimated amount saved through fraud prevention and automated coding checks. Recovery amounts from post-payment audits. Denial rate by reason, first-pass approval rate, and prior auth turnaround time — all trended over time so leadership can see the cumulative financial impact.
What Teams Are Experiencing After Going Live
Each result traces to a specific operational problem — settlement cycles too long, fraud caught too late, denial rates too high. Click through to see what changed.
Book a Claims AI Demo85%
Claims settled within 24 hours — up from 40%. Settlement time dropped from 22 days to under 6. Provider satisfaction up 30 points in one quarter. — Regional Health Insurer, Hyderabad
₹4 Cr
Fraud losses prevented in 6 months. Pre-payment scoring caught suspicious claims before a single rupee went out. — Chief Risk Officer, TPA, Delhi
4%
Denial rate after 3 months — down from 14%. Coding validation caught preventable rejections before submission. — Revenue Cycle Head, 450-bed Hospital, Kochi
75%
Reduction in resolution time. From 30-day cycles to under 8 days — straight-through processing handles routine claims without human review.
Zero
Prior auth backlog after automation. Routine decisions in minutes. Clinical escalations assembled with full context — no digging required.
10×
Increase in analyst productivity. Staff moved from routine data entry to complex cases that actually need human judgment.
Who This Platform Serves
Built for the full ecosystem of health insurance operations — from large insurers and TPAs to government schemes, hospital billing teams, and self-insured employers. Hover or tap to see what it fixes for each.
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Health Insurance Companies
Health Insurance Companies
Processing thousands of claims daily while carrying the cost of manual review and fraud slipping through. AI adjudication and fraud detection directly improve your loss ratio and operational cost.
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Third Party Administrators
Third Party Administrators
Your business runs on processing efficiency. Speed, accuracy, and fraud prevention determine whether clients stay. Our platform delivers all three at the volume and SLA they expect.
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Government Health Schemes
Government Health Schemes
Government schemes face volume and fraud challenges in their most extreme forms. Our platform is built for NHCX standards, ABHA integration, and ICD-10 coding — handling both at scale.
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Hospital Billing & Revenue Cycle Teams
Hospital Billing & Revenue Cycle Teams
The goal: maximum clean claim rates, minimum denials. Our platform catches coding errors before submission, tracks denial patterns, and automates appeals for wrongly rejected claims.
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Corporate Self-Insured Employers
Corporate Self-Insured Employers
Self-insured employers need insurer-grade fraud protection and processing efficiency — without the IT budget. Our platform scales to your employee population.
Built to the Standards That Health Insurance Actually Runs On
Every standard below is scoped during implementation and built directly into the platform — across the data privacy, transaction, coding, regulatory, and security frameworks that govern claims processing in India and globally.
Data Privacy
Healthcare Data Privacy
Foundational data privacy and security frameworks applied to every data store, transmission, and access control in the platform.
Indian Health Insurance
NHCX & Ayushman Bharat
National Health Claims Exchange standards and government scheme integrations for Indian health insurance operations.
Coding Standards
Clinical Coding & Classification
Diagnosis and procedure coding standards the platform validates against at intake, coding review, and pre-adjudication.
Transaction Layer
EDI Transaction Standards
Standards governing how eligibility, claims, remittance, and authorization data move between providers, clearinghouses, and payers.
Security
Security & Audit
Security certifications and audit trail requirements for handling protected health information and claims data at scale.
Cashless & Reimbursement
Both Claim Types Supported
The platform handles both claim types with the workflow variations, turnaround SLAs, and document requirements each demands.
Claims Should Take Minutes, Not Weeks. Fraud Should Be Caught Before Payment, Not After.
Manual review, rule-based fraud tools, and 20-day settlement cycles cost you every day — in overhead, fraud losses, and provider frustration. Our Claims Processing AI is the upgrade that pays for itself.
Book a Claims AI Demo
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Frequently Asked Questions
[ 1 ]
How does the AI know what is fraudulent versus what is just unusual?
The model scores claims on a combination of specific risk signals — historical fraud cases, billing patterns, coding standards, and provider benchmarks — not just whether a claim looks unusual. Every flagged claim includes a transparent explanation of what triggered the alert, so your team decides with context, not guesswork.
[ 2 ]
What coding standards and systems does the platform support?
Supports ICD-10, CPT, SNOMED, and LOINC, aligned with NHCX standards. Integrates with ABHA and Ayushman Bharat claim flows for both cashless and reimbursement types.
[ 3 ]
Can hospitals use this on the provider side for claim submission?
Yes. The provider module validates claims before submission — coding accuracy, completeness, policy eligibility — so hospitals fix issues before the claim reaches the insurer, reducing denials and rework.
[ 4 ]
How long does implementation take?
Most insurers and TPAs go live within 6–10 weeks. Our team handles integration with your claims system and policy database. Fraud models are calibrated on your historical data so they are tuned to your portfolio from day one.
[ 5 ]
What happens to the claims that the AI cannot adjudicate automatically?
They route to your team with a full case summary — claim details, policy clauses, AI recommendation, and why automation was not appropriate. Your team decides with full context. The AI never forces a decision where human judgment is needed.
[ 6 ]
Is the system auditable for regulatory compliance?
Yes. Every decision — automated or human-assisted — is fully logged with the data, rules applied, and outcome. IRDAI requirements for claims documentation and grievance redressal are supported, with the audit trail available at any time.
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