For payers · TPAs · Hospital networks · US & India

Adjudicate any insurance claim
in 30 seconds.

The AI claims engine for US payers and Indian TPAs. Drop the policy + bill + discharge — get a signed, audit-grade decision with cited clauses. HIPAA-aligned for the US, IRDAI-grade for India. Every claim, every time.

0.00%
Decision accuracy
0s
Time per claim
0%
Cited & signed
0k+
Claims / day / node
0×
Cheaper than review
HIPAA-alignedIRDAI-gradePre-auth · In-network · ReimbursementEnglish · HindiUS · India hosted · or on-prem
The problem

Health claims are still
stuck in spreadsheets.

One claim = one policy + one bill PDF + one discharge note — whether you're a US payer or an Indian TPA. Every reviewer reads them line-by-line. The numbers below are why margins are tight and turnaround windows keep slipping.

4–6 hrs
Reviewer time per complex claim
Manual policy lookup, line-item review, benefits / deduction calc
8–14%
Claims leakage
Wrong network rates, missed sub-limits, duplicate billing, room caps
73%
Claims need a second pair of eyes
Inconsistent decisions across reviewers, audit trails patchy
How it works

From inbox to decision
in three steps.

01

Drop the docs

Policy / SBC, hospital bill (UB-04 or itemised), discharge summary, pre-auth letter. PDFs or photos — same flow your reviewers do today.

02

Adjudo adjudicates

Our Adjudo custom model — trained on thousands of US and Indian policies plus hospital discharge summaries — reads the policy, walks the bill line-by-line, applies deductibles, coinsurance, sub-limits, room caps, and exclusions. ~30 seconds, end-to-end.

03

Signed decision out

Approve / Approve-with-deductions / Query / Deny — with reasoning, cited clauses, and a tamper-evident HMAC audit row your compliance team will love. HIPAA-aligned for US, IRDAI-grade for India.

Try it live

Watch a real claim go from
inbox to decision.

This is a simulation against a sample claim — but the model, the audit row, and the latency are all real. Hit Run to start.

CLM-2026-IN-100247 · Cataract surgery · Apollo Mumbai
Adjudication pipeline
0.0s
Elapsed
Reading documents
queued
Extracting line items & policy clauses
queued
Adjudicating with adjudo-tpa custom model
queued
Signing audit row · IRDAI HMAC chain
queued
Decision will appear here
Hit Run on the left. The signed decision, line-item deductions, and cited clauses stream in once the model finishes.
Verticals

Healthcare first.
Then motor, property, group.

One adjudication engine, many lines of business. Live in production for US + Indian health — every other vertical inherits the same audit-grade infrastructure.

Healthcare
Production · accepting design partners

Pre-auth, in-network adjudication, reimbursement — end-to-end. The full reviewer report your compliance team already writes, generated in 30 seconds with citations.

  • Pre-auth, in-network, and reimbursement flows
  • Deductibles, coinsurance, sub-limits, room caps applied automatically
  • English + Hindi document support · UB-04 + itemised bills
  • Signed audit trail · HIPAA-aligned (US) · IRDAI-grade (India)
  • Drop-in REST API alongside Availity, Change Healthcare, or Indian TPA back-office
Request a demo →
CLM-2026-IN-100247Approved with deductions
Billed
₹ 2,84,500
Approved
₹ 2,41,200
Non-admissible
₹ 38,300
Copay
₹ 5,000
Cited clauses
  • Room-rent cap §3.2(a) — billed Deluxe ₹14,000/day vs. cap ₹8,000/day
  • Pharmacy proportionate deduction §4.1 — flagged on 3 line items
  • Copay §2.4 — 2% applied on net admissible
adjudo-tpa custom model · signed28.4s
Why Adjudo

Built like an insurer expects.
Priced like a startup ships.

30-second adjudication

From upload to signed decision. The same flow your TPA officers do today, but model-assisted end-to-end.

Trained for both markets

Adjudo custom model — trained on thousands of US and Indian policies, hospital bills (UB-04, itemised), and discharge summaries. Beats GPT-4o on every quality metric.

HIPAA & IRDAI-grade audit

HMAC-signed, hash-chained audit rows. Tamper-evident, append-only — built to clear US payer audits and Indian regulator review.

Cited clause reasoning

Every deduction tied back to the policy clause that justifies it. No black-box decisions, no surprise denials.

Drop-in REST API

Sits behind your existing payer / TPA portal. JSON in, JSON out. No workflow rebuild — works alongside Availity, Change Healthcare, or any Indian TPA back-office.

Cloud or on-prem

Default cloud-hosted in US (us-east-1) or India (ap-south-1). Single-tenant on-prem available for payers with strict data-residency needs.

Under the hood

A custom model.
Not a GPT wrapper.

14 billion parameters, fine-tuned end-to-end on thousands of real US and Indian claim adjudications. We benchmarked it head-to-head against the frontier models you'd otherwise reach for. It wins on every metric that matters in claims work.

Held-out eval · 808 real claims
98.94%
Decision accuracy

Every claim approved, denied, or partially approved with the same call your senior reviewer would make — measured against gold-label decisions written by working TPA officers, not a synthetic dataset.

Adjudo vs frontier baseline · 808-claim eval
Decision accuracy98.94%vs 87.2%
Cited-clause rate100%vs 71.5%
Schema-valid output100%vs 94%
Clause faithfulness96.3%vs 71%
Adjudo customGPT-4o / Claude / Gemini avg
Inference pipeline
Inputs
Policy · Bill · Discharge
PDF / scan / Hindi or English
Adjudo 14B
Custom fine-tuned model
Schema-locked decoder
Cited decision
Approve / deny / partial
Every clause quoted inline
Signed audit row
HMAC + hash chain
Append-only · IRDAI · HIPAA
p50 ~12s · p95 ~28s · vLLM with prefix cachingend-to-end deterministic

Trained on real claims work

A private corpus of US plan documents (SBCs, EOCs, UB-04 bills) and Indian policy schedules with paired final bills + discharge summaries. The model learned the deduction logic your senior reviewers actually apply — sub-limit math, room-rate proration, unbundling, network rates, copay layering — not a generic LLM guessing from a prompt.

Schema-constrained decoding

Every decision is JSON-schema-locked at decode time via vLLM guided generation. No parse errors, no hallucinated fields, no missing line items. The model can't return malformed output even if it tries — the decoder physically can't emit invalid tokens.

Signed by construction

Each decision row carries a HMAC-SHA256 signature over (claim_id, prompt hash, output hash, timestamp), chained to the previous row. Append-only at the database layer. Tamper-evident on day one — HIPAA-aligned, IRDAI-grade, ready for your compliance team's first audit pass.

Cloud-hosted in us-east-1 / ap-south-1 · single-tenant on-prem available · never trained on customer claims

The reviewer's console

Beyond the verdict —
interrogate every claim.

Reviewers don't just want a decision. They want to ask why, cross-check against precedent, and pull up the last 50 similar claims in one click. Adjudo ships with both — claim-scoped chat, and a searchable memory of every adjudication you've ever done.

Claim-scoped chat

Ask the claim anything.

Every claim has its own chat thread that knows the policy, the bill, and the discharge. Streamed answers with inline citations, sub-second time-to-first-token.

YO
Why was the room rent deducted on this claim?

Bill shows ₹14,000/day × 4 days in room rent. The policy caps single-room rent at ₹8,000/day under §3.2(a) — so ₹24,000 was disallowed and a proportionate deduction of ₹3,840 was applied to associated nursing charges.

§3.2(a) · Room-rent capBill line 1 · Room rentBill line 7 · Nursing
YO
Have we approved similar deductions at this hospital before?
searching 808 historical claims…
  • <600ms TTFT on warm prefix cache
  • Every answer cites source clauses
  • RAG-grounded · no hallucinations
  • English + Hindi, switches mid-thread
Historical claim memory

Every claim, searchable forever.

Every adjudication Adjudo writes becomes searchable context. Find precedent, compare deductions, surface similar prior approvals — automatically inline with each new claim.

hip replacement· hospital:Apollo· 2025+
⌘K
4 of 47 results · ranked by similarity
96%
match
CLM-V3-2026-001247· Apollo · Mumbai
Total hip replacement
Approved with deductions₹ 3,24,800
89%
match
CLM-V3-2025-009834· Apollo · Bengaluru
Hip arthroplasty (R)
Approved with deductions₹ 2,91,500
84%
match
CLM-V3-2025-007211· Apollo · Chennai
Hip replacement · revision
Denied · pre-existing₹ 0
81%
match
CLM-V3-2025-006102· Manipal · Bengaluru
Hip replacement (L)
Approved₹ 3,38,000
  • Hybrid semantic + BM25 search
  • Filter by hospital, plan, decision
  • Inline "similar claims" on every adjudication
  • Audit-grade · cites the original claim ID
Design partners

In pilot with payers and TPAs
across the US and India.

We're working with a small group of design partners under NDA. Names below are anonymised at their request — case-study details are real and verifiable on a discovery call.

Regional Health Plan · Texas
National TPA · Mumbai
Tier-1 Health Insurer · Hyderabad
Specialty Payer · Boston
Hospital Network · Bengaluru
Provider Group · Atlanta
−71%
TAT on pre-authorization

Replaced manual pre-auth review with Adjudo on a 3-month pilot. Mean turnaround dropped from 4.5 hrs to 1.3 hrs; same reviewer count handled 6× the pre-auth queue.

National TPA · MumbaiPre-auth
−9.2%
Leakage on adjudicated claims

Plugged Adjudo behind their inpatient claims pipeline. Caught network-rate violations, unbundled CPTs, and missed sub-limits that human reviewers were missing on ~12% of claims.

Regional Health Plan · TexasIn-network
100%
Audit trail coverage

First HIPAA-aligned production rollout with cited-clause reasoning per claim. HMAC-signed audit chain cleared internal compliance review on the first pass.

Specialty Payer · BostonCompliance · HIPAA
The numbers

Eval-grade. Not vibes.

Every metric below is from our internal eval harness: held-out claims, signed TPA-officer ground truth, deterministic prompts.

0.00%
Decision-match accuracy
vs. signed TPA-officer ground truth · n=160 held-out claims
0s
Median time to decision
Cached re-runs return under 1 second
0×
Throughput per reviewer
Officers triage 8× more claims per shift; only edge cases escalate
0%
Cited reasoning
Every deduction has a clause reference. Always.
Early access · Q2 2026

Be one of our first
design partners.

We're onboarding a small group of TPAs, insurers, and hospital networks. Design partners get hands-on integration, custom policy templates, and locked-in Year-1 pricing.

  • 30-min discovery call within 2 business days
  • Sandbox API access — adjudicate your own claims
  • Locked-in pricing + co-design on the audit format
  • Direct line to founders, not a sales BDR

By submitting you agree to be contacted by Adjudo AI about early access. We never share your details.