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Most UM Programmes Don't Deliver. Ours Does.

Our Utilization Management AI makes every determination evidence-based, auditable, and explainable — automating routine volume so reviewers focus on complex cases.

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Persistent
Yatra
Kellton
Jade Global
Optum
PokerBaazi
Walmart
Turing
BrowserStack
Persistent
Yatra
Kellton
Jade Global
Optum
PokerBaazi
Walmart
Turing

Book Your Free Demo

See it working on your own workflows. We reply within 24 hours.

  • Your idea is 100% protected by our NDA
BrowserStack
Persistent
Yatra
Kellton
Jade Global
Optum
PokerBaazi
Walmart
Turing
BrowserStack
Persistent
Yatra
Kellton
Jade Global
Optum
PokerBaazi
Walmart
Turing

Award-Winning Utilization Management AI

100 Fastest Growth Companies
Global Spring Winner
Top App Development Company
AWS Partner Network
Google Cloud Partner
Highly Rated on Trustpilot
Verified Agency
Top App Development Company
ASSOCHAM Member
100 Fastest Growth Companies
Global Spring Winner
Top App Development Company
AWS Partner Network
Google Cloud Partner
Highly Rated on Trustpilot
Verified Agency
Top App Development Company
ASSOCHAM Member

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.

Utilization Management AI — evidence-based UM at scale

The Same Case Gets Different Decisions

Same guidelines, different outcomes depending on who reviews. Inconsistent interpretation is both an operational and a fairness problem.

Volume Is Growing and Reviewer Capacity Is Not

Volume grows every year, but clinical staff doesn't scale — leaving queues and turnaround times stretching each quarter.

Routine Cases Are Consuming Clinical Reviewer Time

Straightforward cases land in the same queue as complex ones — consuming clinical time without needing a clinician's judgment.

Overutilisation and Underutilisation Are Both Happening

Most UM programmes flag overutilisation but miss the opposite — members who should get care aren't. One direction misses half the problem.

The Audit Trail Is Thin and Documentation Is Inconsistent

When a determination is challenged, manual UM rarely has a clean record — reconstructing the criteria applied is slow and a compliance risk.

The Numbers Behind the Utilisation Management Challenge

Hover to explore the scale of overutilisation, underutilisation, and the AI-driven improvement possible across health insurance UM operations.

How the Platform Works — Across the Full UM Lifecycle

An intelligence layer, not a replacement for clinical judgment.

Prospective Review

Cross-references each submission against your criteria, auto-approves routine cases, and routes complex ones with a structured summary for the reviewer.

What Your UM Team Sees Every Day

Complete operational visibility across every stage of the UM lifecycle.

UM Operations Dashboard
Live view of the full UM queue.
Determination Consistency & Criteria Performance
Spot reviewer variance and appeal overturns.
Utilisation Trend Analytics
Utilisation trends by plan and provider.

Who This Platform Is Built For

Built for insurers, MCOs, TPAs, and government health schemes.

  • Health Insurance Companies

    Health Insurance Companies

    Health Insurance Companies

    AI clears routine UM volume so your team handles complex cases faster.

  • Managed Care Organisations

    Managed Care Organisations

    Managed Care Organisations

    Evidence-based determinations plus analytics to refine criteria and appeals.

  • Third Party Administrators

    Third Party Administrators

    Third Party Administrators

    Scales with your client portfolio, every determination audit-ready.

  • Government Health Schemes

    Government Health Schemes

    Government Health Schemes

    NHCX, ABHA, and IRDAI ready at Ayushman Bharat and CGHS volume.

  • Workers Compensation and Disability Plans

    Workers Compensation and Disability Plans

    Workers Compensation and Disability Plans

    Evidence-based determinations cut legal exposure, every review logged.

Who This Platform Is Built For

Built for insurers, MCOs, TPAs, and government health schemes.

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.

Book a UM Demo
AI Readiness

Award-Winning AI Development & Consulting

2025

100 Fastest Growth Companies

2025

Global Spring Winner

2025

Top App Development Company

2024

AWS Partner Network

2024

Google Cloud Partner

2025

Highly Rated on Trustpilot

2024

Verified Agency

2024

Top App Development Company

2024

ASSOCHAM Member

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 rules — are configured into the guideline library at implementation. Updates take effect immediately across all reviews.

[ 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 full summary and the factors that triggered escalation.

[ 3 ]

How does concurrent review work when clinical information is changing continuously?

The platform monitors active cases through EHR feeds and ADT notifications. When documentation updates, it re-evaluates immediately and flags clinically significant changes.

[ 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 audit trails for regulatory review and grievance redressal.

[ 5 ]

How does the platform support peer-to-peer review between plan physicians and treating physicians?

Peer review requests are logged, assigned, and documented in the platform — each exchange leaves an auditable record of participants and the determination 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, with rates improving over 60–90 days as the AI calibrates to your case mix.

[ 7 ]

What makes this utilization management software different from a standalone utilization review tool?

Our utilization management software covers prospective, concurrent, and retrospective review in one platform. The built-in utilization management AI routes only cases needing clinical judgement to a reviewer, and every determination keeps an audit trail.

[ 8 ]

Does the platform work as utilization review software for managed care organisations and TPAs?

Yes. The same utilization review software serves insurers, managed care organisations, TPAs, and government schemes. Your clinical criteria are configured into the guideline library, so this UM software healthcare teams rely on applies them consistently across every line of business.

[ 9 ]

How does the medical necessity review software keep determinations explainable and auditable?

Every determination from the medical necessity review software cites the specific criteria and clinical factors behind it, never a black box. Each case retains an audit trail of who reviewed it and which guideline version applied — ready for regulatory review, appeals, and peer-to-peer discussion.

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