AWS Professional Services
AI Implementations & Use Cases
Hyperscaler mix
Filter AWS Professional Services's implementations by Microsoft, AWS, or GCP provider evidence.
Reported outcomes
15 cases report measurable results
−70%
Time & speed
median · 9 metrics
−30%
Cost savings
median · 8 metrics
+100%
Risk, reliability & safety
median · 2 metrics
Medians of results published in AWS Professional Services cases, normalized for comparability. See all benchmarks →
All Use Cases (20)
Tangram transforms drug discovery with agentic multi-LLM AI on AWS
Tangram Therapeutics is a UK biotech company focused on solving human disease through computational RNA interference (RNAi) medicines.To accelerate drug target discovery and evaluation, Tangram built LLibra OS, an agentic AI platform that unifies proprietary, licensed, and curated public datasets for research and target-indication assessment.The platform supports retrieval augmented generation, web search, and text-to-SQL to help researchers identify novel targets, evaluate therapeutic potential, and design medicines.
OpenCampus builds AI-native education solutions using Amazon Bedrock
OpenCampus is an education technology company providing an open source, no-code, AI-native SaaS platform for universities across Europe.The company needed a scalable, GDPR-compliant cloud foundation that could handle semester demand spikes and support easier onboarding without requiring deep cloud infrastructure expertise.OpenCampus adopted AWS infrastructure and Amazon Bedrock to add generative AI capabilities while letting universities choose compliant foundation models through parameterized AI calls.The platform also automates infrastructure setup for new customers and supports demo environments and campus management workflows through its no-code system.
CSL reinvents technology modernization with agentic AI using Amazon Q Business and AWS Transform for VMware
CSL is a global biotechnology company modernizing its business-critical operations by exiting legacy on-premises infrastructure and moving to the cloud.The company faced technical debt across 29 data centers, with 5,000 VMware servers and more than 1,000 applications, plus fragmented documentation and complex dependencies that slowed migration planning.CSL used Amazon Q Business to index more than 17,000 pages of infrastructure requirements and AWS Transform for VMware to analyze VMware environments, map dependencies, and generate migration wave plans.The company is also using AWS for RISE with SAP as part of its broader modernization program.
KYTC modernized customer contact center with Amazon Connect Customer to reduce call duration and training time
Kentucky Transportation Cabinet (KYTC) modernized its contact center solution in 6 weeks using Amazon Connect Customer, Amazon Connect Wisdom, Amazon Connect Cases, Amazon Connect Agent Workspace, and Amazon Connect Customer Profiles.The agency serves 4.1 million drivers in Kentucky, providing customer service for vehicle licensing and taxes. The prior contact center was unreliable during peak volume and required expensive third-party consulting.
GWM Modernizes Security Compliance Development with Amazon Q Developer on AWS China (Ningxia)
GWM modernized its security compliance system for multi-cloud governance across 14 global cloud environments by migrating the system to AWS China (Ningxia).The security team used Amazon Q Developer to refactor the development workflow, generate code in multiple languages, and support a security left-shift approach for earlier issue detection.The new architecture includes scanner data collection, analyzer risk detection, and tenant-isolated reporting, supported by Amazon Kinesis, Amazon Aurora MySQL, Amazon OpenSearch Service, Amazon EKS, and AWS Graviton4.
Bosch Mobility Platform & Solutions builds L.OS and plans AI-driven logistics experiences with AWS
Bosch Mobility Platform & Solutions, a division of Bosch, built the Logistics Operating System (L.OS) with AWS to digitize fragmented trucking and logistics workflows, enable automation across providers, and support sustainability goals.The platform uses an AWS landing zone based on AWS Control Tower, integrated regionally, and the company also built RevX on AWS using Amazon API Gateway and Amazon ECS to unify load-board data for fleet dispatchers. A chatbot POC is planned using Amazon Bedrock and Amazon Q.
CANAL+ Group: Generative AI chatbot and AI Factory using Amazon Bedrock (training + POCs)
CANAL+ Group modernized its AWS environment to accelerate generative AI adoption for the myCANAL platform, including speech-to-text, natural-language search, and chatbot enhancements.Working with AWS Training and Certification and AWS experts, the company built cloud skills, ran a hackathon for rapid proof-of-concepts, and applied guardrails for responsible generative AI.CANAL+ also created an internal AI Factory for the Gender Equality Monitoring framework, using Amazon S3 and ML workflows to surface insights on gender representation.
Booking.com uses Amazon SageMaker and Amazon Bedrock to power personalized travel recommendations
Booking.com uses AWS to handle more than 150 petabytes of data and apply generative AI and fine-tuning to deliver relevant, personalized travel suggestions.The company collaborated with AWS Professional Services to build a scalable machine-learning framework that accelerates experimentation and innovation for destination and accommodation recommendations.The article presents Booking.com as using AWS to improve booking services globally across its travel marketplace.
Availity Modernizes Healthcare Technology through Collaboration with AWS (Amazon Q for RCM)
Availity, the largest real-time health information network in the U.S., is modernizing its revenue cycle management application on AWS to improve resiliency, security, and performance.The company migrated and phased the RCM application to AWS with help from AWS Professional Services and the Experience-Based Acceleration (EBA) framework, while also upskilling engineers through AWS Training and Certification, AWS Skill Builder, and AWS Cloud Quest.Availity implemented Amazon Q Developer, Amazon Q Business, and Amazon Q in QuickSight to improve development workflows, automate release review analysis, and help non-technical users consume data more easily.
Availity increases productivity and accelerates code development with Amazon Q
Availity, a large real-time health information network, used Amazon Q Business, Amazon Q Developer, and Amazon Q in QuickSight to improve access to enterprise knowledge, accelerate software development, and make data analysis faster across teams.The company faced scattered code and documentation across multiple repositories, which made it difficult for employees to find relevant information for release management, code reviews, and analytics.
Froedtert & the MCW Health Network modernized patient experience on AWS and plans Bedrock generative AI
Froedtert & the MCW Health Network, through its Inception Health innovation arm, built a digital platform on AWS to reimagine the patient experience and support personalized digital engagement.The organization wanted a lean, secure, HIPAA-compliant cloud foundation that could connect disparate parts of the patient journey, support telehealth and asynchronous care at scale, and enable data-driven patient communications.
Jabil Drives Manufacturing Efficiency and Process Optimization with AWS Generative AI
Jabil is a global manufacturing and supply chain solutions provider with over 100 sites worldwide.Jabil addressed data fragmentation and improved operational efficiency using AWS cloud and generative AI solutions.Migrated 400+ applications to AWS and centralized data in a data lake for analytics and AI.Developed generative AI applications including an intelligent shop floor assistant chatbot powered by Amazon Q Business for real-time diagnostics in multiple languages.Built intelligent customer research and procurement assistants for enhanced decision-making.Results include 67-83% reduction in deployment times, 74% reduction in data processing times, 23% cost savings with serverless integration, and improved troubleshooting accuracy.
KONE Unlocks New Efficiencies Using AWS IoT
KONE, a global leader in elevator and escalator industry, built a robust and scalable IoT platform using AWS IoT Core and related services to connect and monitor a growing fleet of smart devices.The challenge was to improve operational efficiency, reduce maintenance callouts, and support a large device base with highly available cloud architecture.The solution involved migrating to AWS IoT Core, AWS IoT Device Management, AWS IoT TwinMaker, Amazon Simple Storage Service, and AWS Professional Services to enable near-real-time monitoring, provisioning, and predictive maintenance.The impact included a 40% reduction in customer-reported issues and entrapment incidents, improved provisioning success near 100%, device fleet scale increasing from 100K to 500K, and foundation for AI and digital twin innovations.
Legal & General modernizes pension document processing with Amazon Textract and Amazon SageMaker
Legal & General's UK retail retirements division modernized its pension document ingestion process on AWS to handle thousands of paper forms each day.The solution was designed to improve document processing speed, compliance with service-level agreements, and staff productivity.
Georgia-Pacific Optimizes Operator Efficiency with Generative AI Using Amazon Bedrock
Georgia-Pacific, a leading global manufacturer of pulp and paper products, faced challenges with scattered knowledge across many facilities, leading to production inefficiencies and risk of knowledge loss from retiring employees.The company partnered with AWS and AWS Professional Services to develop ChatGP, a generative AI chatbot using Amazon Bedrock's Anthropic Claude large language model, integrated with IoT sensor data via Amazon Kinesis.ChatGP provides machine operators centralized, contextualized, and real-time troubleshooting guidance and knowledge access tailored to specific equipment and processes across 140+ facilities.Impact includes improved machine production, reduced quality defects, minimized downtime, accelerated troubleshooting, preservation of expert knowledge, and estimated multimillion-dollar annual savings across operations.
CDPHP Modernizes Medical Data Processing and Improves Care with AWS AI and ML
Capital District Physicians' Health Plan Inc. (CDPHP) struggled with manual processing of unstructured medical records for deriving insights to improve care.CDPHP deployed an automated, modular, serverless AI/ML pipeline on AWS using Amazon Textract to extract data, Amazon Comprehend Medical to extract and normalize medical info, and Amazon SageMaker for ML model development.The solution improved processing speed and accuracy, automating 3,000 records weekly with plans to double volume, cutting HEDIS report generation from 4-5 days to twice daily, and increasing efficiency by 60%.
Alabama Department of Revenue and Wisconsin Department of Revenue modernize contact centers with Amazon Connect and Amazon Q in Connect
State tax agencies modernized legacy contact centers to handle seasonal surges, reduce manual work, and improve resilience for sensitive taxpayer inquiries.ALDOR deployed an AI-enabled IVR in eight days; Wisconsin DOR launched a modernized Amazon Connect contact center in under four months and added Contact Lens and Amazon Q in Connect for analytics and source-cited answers.
A*STAR Develops AI-powered Logistics Agent with AWS to Transform Supply Chain Operations
A*STAR's Advanced Remanufacturing and Technology Centre (ARTC) collaborated with AWS Professional Services to develop a Logistics Agent powered by Amazon Bedrock to address supply chain complexity and scattered data.The AI agent integrates data from multiple systems including ERP, WMS, and TMS, enabling natural language processing to provide real-time logistics information, automate tasks and improve decision-making.The solution reduces manual lookup workloads by up to 50%, decreases expedite costs by 3%-5% of logistics spend, and improves planner productivity and customer satisfaction through predictive insights and rapid updates.
Electronic Caregiver (ECG) accelerates telehealth analytics using AWS Health Data Accelerator (Amazon Q in QuickSight)
Electronic Caregiver Inc. (ECG), a New Mexico–based digital health company, implemented the AWS Health Data Accelerator to build a secure, scalable analytics platform for EHR, patient survey, and medical IoT data.The solution enabled ECG to ingest more than two million patient records into AWS and provide governed dashboards for monitoring, financial forecasting tied to insurance reimbursements, and patient outreach analytics.ECG also used Amazon Q in QuickSight for natural-language access to insights and executive summaries, reducing dependence on internal coding and analytics teams.
Coinbase boosts efficiency and accelerates development by collaborating with AWS
Coinbase collaborated with AWS teams including AWS Professional Services to drive multiple cloud optimization initiatives.The work focused on migrating legacy workloads to Amazon EKS, improving scalability and reliability, and accelerating developer iteration.