Amazon Bedrock
Fully managed service for accessing foundation models from leading AI companies via AWS.
16
Use Cases
16
Companies
9
Industries
Companies Using Amazon Bedrock
Industries
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Use Cases (16)
Tabnine integrated Claude 3.5 Sonnet via Amazon Bedrock into its AI coding assistant, serving over 1 million monthly developers. The migration delivered 50% faster response times, a 20% increase in free-to-paid conversions, and a 20-30% reduction in churn—while meeting strict security and compliance requirements for regulated industries.
ASAPP is an AI-native customer service platform that orchestrates large language models to automate contact center interactions for enterprise clients. By deploying Anthropic’s Claude through Amazon Bedrock, ASAPP eliminated its homegrown PII redaction layer and reduced call escalations by up to 40%, while helping clients achieve a 91% first-call resolution rate. The platform now automates more than 90% of contact center interactions, with human agents freed to handle three times the volume of complex cases.
Pinterest built an AI-powered discovery engine on AWS processing 18TB daily, delivering 10 million AI recommendations per second across 10,000+ GPU instances, driving 17% revenue growth and 70% AI-driven discovery.
Thomson Reuters integrated Claude via Amazon Bedrock into its AI platform, CoCounsel, to make the expertise of 3,000+ subject matter experts and 150 years of authoritative content accessible to legal and tax professionals. The solution combines Retrieval-Augmented Generation (RAG) architecture with multi-model deployment to deliver comprehensive, accurate professional analysis. Early adopters report dramatic efficiency gains, with some estimating task time cut in half or more.
Omnicom is one of the world’s largest marketing communications networks, with 75,000 employees serving over 5,000 clients across 70+ countries. The company migrated nine global data centers to AWS and built an AI-powered platform on Amazon Bedrock and Amazon SageMaker to deliver hyper-personalized campaigns at scale. The migration cut compute infrastructure costs by 90% while enabling real-time processing of 400 billion daily marketing events.
Petrobras applied generative AI and intelligent automation to its tax department, feeding 150 pages of Brazilian tax regulations and three months of financial data into a model built on Automation Anywhere, Amazon Bedrock, and Amazon SageMaker. In three weeks, the system identified $120 million in tax savings and filed taxes within three days—the first time in 15 years the team avoided weekend work during tax season. The company projects over $1 billion in total savings by year-end.
Vectorize.io is a US-based software company that builds agentic and generative AI infrastructure, helping organizations in law, insurance, and finance make vast volumes of unstructured data usable by large language models. By integrating Elastic’s hybrid search and Elastic Cloud Serverless with Amazon Bedrock, Vectorize deploys production-ready AI solutions for clients in hours rather than weeks. One client whose developer community grew by a million users in a year relied on Vectorize’s real-time learning agent—built on Elasticsearch—to answer support queries and instantly index new answers for future use.
TaskUs is a leading outsourced digital services company providing next-generation customer experience (CX) for innovative global brands. To move beyond flat-file embedding storage and scaling limitations, TaskUs built TaskGPT—a proprietary GenAI platform—with Pinecone as the core vector database for semantic search, RAG-based knowledge retrieval, and client-specific recommendations. The result: a 20% reduction in average handle time and a 5% increase in customer satisfaction across client deployments.
AppFolio is a real estate management platform serving 20,000+ customers and 8 million+ units under management. After building Realm-X Messages—an LLM-powered inbox for property managers—on Amazon Bedrock, AppFolio used Datadog LLM Observability to identify bottlenecks and cut latency by 80–90%, which drove a 300% increase in product adoption and saves property managers an average of five hours per week.
Blue Origin deployed 2,700+ AI agents with 70% company-wide adoption, achieving a 90% reduction in hardware development time using Amazon Bedrock.
Nomura Research Institute deployed Claude 3.5 Sonnet via Amazon Bedrock to automate complex Japanese document analysis, cutting review times by 50% for clients in financial, manufacturing, and distribution sectors.
N26 deployed Claude via AWS Bedrock across 15+ internal use cases in its first year, automating up to 70% of tasks in targeted customer service processes and cutting manual processing by 50% across 24 European markets. New AI implementations now go from ideation to evaluation in 1–2 weeks.
UOL Group is Brazil’s largest digital media, technology, and payments platform, serving eight out of ten Brazilian internet users monthly across more than 200 applications and thousands of cloud and on-premises resources. After migrating from Splunk to Elastic Security and deploying Elastic AI Assistant and Attack Discovery with Amazon Bedrock integration, UOL reduced security incident resolution time by 80% — from days to minutes — and cut false positive alert volume in half.
Intuit integrated Claude via Amazon Bedrock into its Intuit Assist feature within TurboTax to generate plain-language explanations of tax calculations. The integration combines Claude's natural language capabilities with Intuit's proprietary tax knowledge engine, serving millions of customers during peak tax season. The result was higher helpfulness ratings and improved completion rates for federal tax filings.
Cox Automotive deployed 17 production AI agent solutions using Amazon Bedrock AgentCore, reducing estimate completion from 48 hours to 30 minutes, achieving 3x consumer response rates, and projecting 17,000 hours saved.
Postman selected Claude Opus 4.6 as the default model for Agent Mode, saving developers up to 1,150 hours per year and nearly $1M annually for a 10-person team in API development automation.