# How Jindal Healthcare cut analytics costs by 90% with Supaboard

> An RCM provider unified claims, payer and denial data across every client, and moved analysis from four hours to two minutes.

HTML version: https://supaboard.ai/case-study/jindal-healthcare

- Company: Jindal Healthcare
- Industry: Healthcare / RCM
- Headline result: 90% lower analytics costs
- Published: 2026-01-22

## About Jindal Healthcare

Jindal Healthcare is a US revenue cycle management operator, headquartered in Houston, Texas, that now goes to market through ANKA — its AI revenue-cycle platform. ANKA takes on the whole post-submission cycle: denial management, underpayment recovery and AR follow-up, reading EOBs, writing and filing appeals, disputing underpayments and chasing payers, with people handling the exceptions. It serves physician groups of 10 to 50-plus providers, community and rural hospitals, PE-backed healthcare organisations and in-house revenue cycle departments. The company states it manages 300+ providers across its portfolio, has processed over $1B in claims, brings more than a decade of RCM operating experience, and reports 100% client retention. It is HIPAA compliant and SOC 2 certified, and sells on performance-based pricing backed by SLAs.

## The problem

- Every client is its own dataset — distinct claims data, payer mix, denial patterns and reporting expectations, multiplied across the roster.
- A senior-analyst bottleneck. Answers needed someone who could write, run and reconcile SQL across systems that were never designed to talk.
- Reconciliation overhead. Numbers had to be stitched together by hand every time a question crossed two systems.
- Four hours per question. At that cost analysis was rationed, saved for problems the team already knew were problems.

## Results

| Figure | What changed |
| --- | --- |
| 90% | Reduction in analytics cost across RCM operations |
| 4 hrs → 2 min | Per-client analysis, fast enough to run on demand |
| Every client | Claims, payer and denial data unified into one source of truth |

## The story

Jindal Healthcare operates in revenue cycle management — one of the most
data-heavy corners of healthcare. Every RCM client brings its own claims data,
payer mix, denial patterns, and reporting expectations. Multiply that across a
client roster and the analytics workload becomes its own operations problem.

With Supaboard, Jindal unified RCM data across clients into one source of truth.
The trainable agent learned the domain — claim lifecycles, denial categories,
payer behaviours, and the difference between aging that signals a process
problem and aging that's just how a payer pays.

## When answering questions costs as much as the work

A single client analysis used to take four hours. The work was spread across
multiple analysts, multiple SQL queries, and multiple reconciliations between
systems that were never designed to talk to each other. At four hours a
question, analysis gets rationed: you save the deep look for problems you
already know are problems.

## One source of truth, trained on RCM

Supaboard unified Jindal's RCM data across clients and learned the domain, so
analysis stopped depending on who was free to write the query:

- **Unified across clients:** All claims, payer, and denial data in one trusted
  source instead of scattered systems.
- **Trained on the domain:** Supaboard learned claim lifecycles, denial
  categories, and payer behaviours — including when aging is a process problem
  versus just how a payer pays.
- **Anyone can ask:** Analyses that required a senior analyst became
  conversations any operator could have with the data directly.

## From four-hour SQL builds to two-minute answers

What used to mean opening a ticket, waiting for an analyst, and reconciling
outputs now happens in a single question. Analyses that took four hours now take
two minutes — and analytics cost dropped 90%. The query layer, the
reconciliation, and the senior-analyst time all collapse into a conversation any
operator can have with the data directly.

## Investigating at the speed of curiosity

What changed wasn't just speed — it was which questions became askable. When a
deep look cost four hours, the team saved it for known problems. When it costs
two minutes, anyone can chase a hunch. Denial root-cause work, client reviews,
and benchmarking now start from curiosity, not from whatever the analytics queue
had time for.

## Where Jindal Healthcare landed

Jindal Healthcare now runs RCM operations on Supaboard. The change shows up
across the team's day-to-day:

- **90% lower analytics cost:** Answering questions no longer rivals the cost of
  the work the answers inform.
- **Four hours to two minutes:** Per-client analysis is fast enough to run on
  demand.
- **More questions, answered:** The team investigates freely instead of
  rationing what it can look into.

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