Apexon offers an AI-powered claims management solution for US healthcare providers and hospital revenue cycle teams to reduce claim denials and recover lost revenue.The solution applies AI across the claims lifecycle, including automated claim scrubbing, denial prediction, payer note analysis, and automated appeals.It is built on Amazon HealthLake, Amazon SageMaker, Amazon Bedrock, Amazon Comprehend Medical, and Amazon Textract, with HIPAA-aligned controls using AWS IAM, AWS KMS, Amazon Macie, and AWS CloudTrail.
Use case type
Claims automation
Automates the intake, triage, and adjudication of insurance claims to speed settlement and cut manual work.
127
60
6
19 mo
Adoption over time
Documented cases per month
By case publish month · completed months only
81 cases documented across 37 months (Jul 23 – Jul 26), peaking at 7 in June 2025.
30 earlier cases before Jul 23 not shown
Each column counts every documented case of this type by its publish month, across the full corpus. The in-progress current month is excluded from columns and surfaced separately, and cases published before the charted window are summarized as earlier cases instead of plotted.
Company examples
Use cases of this type
10 shown from 127 use cases
UCARE.AI shortens healthcare claims product release cycle to one week using Vertex AI and Gemini Pro
UCARE.AI is a Singapore-based insurtech company that moved from a cloud-agnostic setup to Google Cloud to improve product development and access the latest generative AI capabilities.The company uses Vertex AI, Gemini Pro, MedLM, BigQuery, Google Kubernetes Engine, Cloud Storage, Cloud SQL, and Pub/Sub to support healthcare claims analytics, fraud detection, and claim assessment workflows.
Anthem used Amazon Textract to digitize and automate claims processing for submitted medical claim documents.The solution extracts printed text, handwriting, tables, and forms from scanned documents and classifies them into a digital-processing workflow.
Visma, through M2 by Visma, built M2 Tarkka to automate validation of travel and expense claims on AWS.The solution combines deterministic rules with LLM-powered checks to interpret contextual free-text descriptions and apply Finnish tax and policy rules.Visma also added an AI agent so customers can upload travel policies and ask natural-language questions with source-attributed answers.
Gallagher: AI as a force multiplier for trusted advisors (claims summarization + quote automation)
Gallagher, a global insurance broker and risk management firm, built an AI platform on Microsoft Foundry to support secure enterprise AI in a highly regulated environment.The company deployed Microsoft 365 Copilot across 70,000 employees and used Copilot Studio to create governed agents connected to internal systems.AI is applied to claims summarization, document-heavy workflows, multi-line quote letter automation, and RFP automation with human oversight and strict data boundaries.
This article describes a hands-free first notice of loss (FNOL) intake prototype for insurance claims.It combines Strands Agents for insurance-specific reasoning with Amazon Bedrock AgentCore Browser Tool and Amazon Nova Act to operate existing portals, tag multimodal evidence, and produce decision-ready intake for adjusters.
Insurance Claims Processing Solution (AWS Marketplace) using Textract/Comprehend + Bedrock/SageMaker
AWS native claims automation solution enabling faster validation, fraud detection, and compliance driven adjudication across automobile and property insurance workflows.The solution modernizes claims adjudication by automating document validation, policy alignment, fraud detection, and compliance checks across high volume automobile and property insurance workflows.It standardizes decision logic and accelerates claim processing while preserving auditability.
UNIQA SEE accelerates health insurance claims processing with Azure AI + Azure Document Intelligence + Azure OpenAI
UNIQA SEE faced fragmented and complex medical referral letters and invoices, heavy manual document review and validation, call center reliance, and long claims processing cycles.
UCARE.AI shortens healthcare claims product release cycle to one week using Vertex AI and Gemini Pro
UCARE.AI is an AI-driven insurtech company in Singapore focused on healthcare claims. It moved from multi-cloud to Google Cloud to streamline product development and gain access to generative AI capabilities.Its solutions include AlgoDetect for flagging outlier claims to reduce fraud, waste and abuse, and AI Assessor for drafting summaries and responses using Gemini Pro and MedLM for medical terminology understanding.The company says the move to a single cloud shortened its product release cycle from one month to one week and improved time savings for customers reviewing flagged claim details.
Artificial Labs AI claims automation using Gemini Enterprise Agent Platform (Conscium & OQC case study)
Artificial Labs used Google Cloud to build insurance claims automation that recognizes patterns in complex insurance documentation and moves risks toward quote readiness with humans in control.Conscium, Artificial Labs, and Oxford Quantum Circuits also used Google Cloud to manage thousands of LLM requests efficiently and support adjacent AI evaluation and quantum workloads.The implementation centers on Gemini Enterprise Agent Platform, Gemini for Google Cloud, and BigQuery as the data and analytics foundation.
Common questions
Claims automation at a glance
- How many claims automation use cases are documented?
- The AI Use Case Hub documents 127 real claims automation deployments across 6 industries, with 60 detailed company examples you can browse.
- Which industries adopt claims automation the most?
- Claims automation is most common in Insurance (88%), Healthcare (6%) and Finance (2%).
- Which countries lead in claims automation?
- United States leads documented claims automation deployments, followed by Germany and United Kingdom.
- What technologies are used for claims automation?
- Teams most often build claims automation with Azure OpenAI, Azure AI and Azure.
- What AI capabilities power claims automation?
- Across the documented deployments, the most common capability patterns are Agent (27%), Vision (14%) and Copilot (13%).
- What results do companies report from claims automation?
- Across the 127 deployments reporting outcomes, companies most often cite speed & agility (68%), new product / capability (63%) and customer experience & trust (61%). Where impact is quantified, the strongest evidence is in time & speed: a median −60% across 14 reported metrics.