The Same Case Gets Different Decisions
Same guidelines, different outcomes — depending on who reviews the case. Inconsistent interpretation is both an operational and a fairness problem.
Most UM Programmes Don't Deliver. Ours Does.
Every determination evidence-based, auditable, and explainable. Our Utilization Management AI automates routine volume and frees clinical reviewers to focus where their expertise matters most.
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The Real Problems Inside Every UM Programme
UM goals are right. The execution — in most health plans — is broken. Each failure compounds into reviewer burnout, provider frustration, and inconsistent determinations.
Volume Is Growing and Reviewer Capacity Is Not
Volume grows every year. Clinical staff doesn't scale with it — leaving queues behind and turnaround times stretching each quarter.
Routine Cases Are Consuming Clinical Reviewer Time
Straightforward cases still land in the same queue as complex ones — consuming the same clinical time without needing a clinician's judgment.
Overutilisation and Underutilisation Are Both Happening
Most UM programmes flag unnecessary procedures — but miss the equal and opposite problem: members who should be receiving care aren't getting it. Looking in only one direction misses half the failure.
The Audit Trail Is Thin and Documentation Is Inconsistent
When a determination is challenged by a provider, member, or regulator, manual UM rarely has a clean record. Reconstructing what criteria were applied and why is slow, incomplete, and a compliance and legal risk.
How the Platform Works — Across the Full UM Lifecycle
An intelligence layer — not a replacement for clinical judgment. Every UM determination, automated or human-reviewed, is grounded in the same evidence and applied against the same criteria.
What Your UM Team Sees Every Day
Complete operational visibility across every stage of the UM lifecycle — prospective, concurrent, and retrospective — with the analytics your clinical leadership needs to manage capacity, quality, and performance in real time.
UM Operations Dashboard
Live view of the full UM queue — by case status, type, clinical urgency, and reviewer assignment. Auto-approved, pending, escalated, and info-pending cases in one place. Auto-determination rate, reviewer workload, and turnaround trends at a glance.
Determination Consistency & Criteria Performance
See where human reviewers diverge on similar clinical presentations and which criteria drive the highest variance. Identify which denials are overturned most on appeal — so you can update guidelines before inconsistency becomes a regulatory concern.
Utilisation Trend Analytics
Admission rates, length of stay, procedure utilisation by diagnosis, and care setting appropriateness — broken down by region, plan type, and provider. Overutilisation and underutilisation visible simultaneously, with care gap alerts feeding into care management programmes.
What UM Teams Are Seeing After Going Live
Each result traces to a specific failure — inconsistency, backlogs, or determinations that couldn't survive appeal. Click through to see what changed.
Book a UM AI Demo78%
Of routine prospective cases auto-determined — up from zero. Clinical reviewers now focus exclusively on cases that need their judgment. — Regional Health Insurer, Hyderabad
4 hrs
Average turnaround for prospective determinations — down from 3.2 days. Provider satisfaction improved 40 points in one quarter. — Managed Care Organisation, Chennai
61%
Reduction in appeal overturn rate after 6 months. Consistent, fully documented determinations are harder to challenge. — TPA, Delhi
5.2%
Reduction in medical spend in year one — overutilisation flagged at prospective review, including unsupported procedures and inappropriate care settings.
100%
Audit-ready documentation on every determination. Complete case records assembled in minutes when regulators or providers challenged a decision.
3×
Increase in clinical reviewer capacity — same team, three times the volume, with routine cases removed from the queue and complex cases arriving with a structured summary.
Who This Platform Is Built For
Built for the full UM ecosystem — national insurers, managed care organisations, TPAs, government schemes, and workers compensation plans.
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Health Insurance Companies
Health Insurance Companies
AI-powered UM handles routine volume automatically, ensures consistency at scale, and gives your clinical team the tools to manage complex cases faster — with population-level analytics to drive strategic improvement.
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Managed Care Organisations
Managed Care Organisations
Consistent, evidence-based determinations and the analytics to continuously improve them — driving criteria refinement that improves quality metrics, utilisation benchmarks, and appeals outcomes quarter over quarter.
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Third Party Administrators
Third Party Administrators
Scales with your client portfolio without growing reviewer headcount. Every determination is fully documented — so when a client requests a UM audit, the data is ready.
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Government Health Schemes
Government Health Schemes
Built to NHCX standards, ABHA integration, and IRDAI compliance. Consistent, documentable determinations at the volume and scrutiny Ayushman Bharat, CGHS, and state schemes demand — every case reviewed against the same criteria, regardless of region or provider.
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Workers Compensation and Disability Plans
Workers Compensation and Disability Plans
Evidence-based determinations reduce legal exposure from errors while improving clinical appropriateness. Every peer review and appeals exchange is logged with a complete audit trail.
Built to the Standards That Utilisation Management Actually Runs On
Every standard is scoped at implementation and built directly into the platform — clinical guidelines, IRDAI requirements, data privacy, interoperability, and audit trails.
Clinical Guidelines
Evidence-Based Guideline Support
Major evidence-based frameworks maintained centrally and updated as guidelines evolve.
Indian Regulatory
IRDAI & Government Scheme Compliance
Built into determination documentation, audit trails, and government scheme integrations for Indian health insurance UM.
Data Privacy
Healthcare Data Privacy
Privacy and security frameworks across every clinical record, determination, and reviewer interaction.
Interoperability
Clinical Data Integration Standards
EHR systems, ADT feeds, clinical documentation, and payer admin systems — so the platform has the clinical data it needs, when it needs it.
Audit & Security
Audit Trail & Security Certifications
Immutable audit trails for every determination — automated or human — with security certifications for protected health information at scale.
Coding Standards
Clinical Coding & Classification
Coding standards validated on every clinical submission — ensuring determinations rest on accurate, standardised classification.
Right Care. Right Patient. Right Time. At Any Volume.
Manual UM can't be consistent, fast, and fully documented at scale. AI-powered UM can — and plans investing now are building a compounding advantage in cost, quality, and provider relations.
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Frequently Asked Questions
[ 1 ]
How does the AI apply our specific UM criteria rather than industry defaults?
Your criteria — MCG, InterQual, proprietary guidelines, IRDAI, or scheme-specific rules — are configured into the platform's guideline library at implementation. When guidelines update, the change takes effect immediately across all reviews. No reviewer ever works from a superseded version.
[ 2 ]
What happens when the AI cannot make a confident determination?
Every case gets a confidence score. Below your threshold, it routes to a clinical reviewer with a complete summary, relevant criteria, and the factors that triggered escalation — never a blank intake form.
[ 3 ]
How does concurrent review work when clinical information is changing continuously?
The platform integrates with EHR feeds, ADT notifications, and clinical documentation systems to monitor active cases in real time. When documentation updates, it re-evaluates immediately and flags clinically significant changes. Case managers always see current status — not a first-review snapshot.
[ 4 ]
Is the system compliant with IRDAI regulations and Indian market requirements?
Yes. Built to IRDAI clinical review requirements, NHCX data standards, and ABHA-compatible records with full audit trails for regulatory review and grievance redressal. Ayushman Bharat and state scheme UM requirements are supported in implementation configuration.
[ 5 ]
How does the platform support peer-to-peer review between plan physicians and treating physicians?
Peer review requests are logged, assigned, scheduled, and documented within the platform. Every exchange creates a complete, auditable record of who participated, what was discussed, and what determination was reached.
[ 6 ]
How quickly do we see improvement in auto-determination rates and reviewer efficiency?
Most plans see meaningful auto-determination from the first week. Rates improve over 60–90 days as the AI calibrates to your population and case mix. Reviewer time savings are typically visible within the first month as routine volume shifts out of the human queue.
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