List of AWS Bedrock Customers
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Since 2010, our global team of researchers has been studying AWS Bedrock customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased AWS Bedrock for Generative AI Platforms from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using AWS Bedrock for Generative AI Platforms include: Ericsson, a Sweden based Communications organisation with 88826 employees and revenues of $236.68 billion, BMW, a Germany based Automotive organisation with 157457 employees and revenues of $165.84 billion, Sony, a Japan based Manufacturing organisation with 113000 employees and revenues of $93.01 billion, AstraZeneca, a United Kingdom based Life Sciences organisation with 96100 employees and revenues of $79.71 billion, Cox Automotive, a United States based Professional Services organisation with 29000 employees and revenues of $23.00 billion and many others.
Contact us if you need a completed and verified list of companies using AWS Bedrock, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The AWS Bedrock customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Aderant | Professional Services | 700 | $164M | United States | Amazon Web Services (AWS) | AWS Bedrock | Generative AI Platforms | 2023 | n/a |
In 2023, Aderant deployed AWS Bedrock to embed generative AI capabilities within its Generative AI Platforms stack for Expert Sierra operations. The implementation operates inside a multi-region, tenant-isolated AWS account architecture that supports a 260+ tenant production fleet serving North America, Europe, and APAC, and is managed as infrastructure as code and identity-federated cloud infrastructure.
Aderant runs Claude Code against AWS Bedrock for tenant-isolated inference inside its account boundary, maintaining dedicated IAM configurations, centralized logging and cost controls per tenant. The implementation packages AI-augmented operations into agentic troubleshooting workflows and reusable Claude Code skills that execute tenant lookup, log triage, drift checks, and root-cause analysis across AWS, Active Directory, and SQL Server.
Infrastructure modules implemented include Terraform-driven per-tenant EC2, AMI, storage and networking modules deployed across regions, fleet-wide configuration management via Ansible AWX and Chef, and orchestration using EC2, Lambda, Step Functions, EKS with Karpenter, FSx, Secrets Manager, SSM, CloudWatch and Athena. Automation is polyglot, with PowerShell modules PSExpertSierra and PSExpertSierraMonitor packaged via Jenkins and Azure DevOps Artifacts, plus Python and Bash tooling, and an early Claude integration generating Ansible YAML with human in the loop review.
Integrations and operational coverage extend to Okta federated identity tied to Azure, Okta Workflows leveraging OAuth2 and JWT for remote secret rotation, Windows Server and AD management including domain joins and gMSA, SQL Server host rebuilds and migrations from 2016 to 2022 driven from Terraform through validation, and cross functional handoffs with DBA and client teams. Governance is enforced through tenant isolation, IAM and logging controls, cost governance, runbook-driven automation and packaged institutional knowledge to enable repeatable, infrastructure aware workflows within Aderant's Generative AI Platforms deployment of AWS Bedrock.
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AstraZeneca | Life Sciences | 96100 | $79.7B | United Kingdom | Amazon Web Services (AWS) | AWS Bedrock | Generative AI Platforms | 2025 | n/a |
In 2025, AstraZeneca deployed AWS Bedrock as part of a Generative AI Platforms implementation to power Development Assistant, a multi-agent AI application used across clinical development, regulatory, patient safety, and quality functions. Development Assistant uses conversational natural language queries to surface actionable insights from both structured and unstructured R&D data, reducing the time to answer complex questions from hours to minutes. This implementation positions AstraZeneca AWS Bedrock Generative AI Platforms to accelerate decision making across its drug development pipeline toward the company’s 2030 objectives.
The solution architecture centers on a multi-agent design enabled by Amazon Bedrock Agents, with a supervisor agent routing prompts to specialized subagents such as terminology, clinical, regulatory, and database agents. Development Assistant combines text-to-SQL generation with retrieval-augmented generation to translate domain queries into executable queries against standardized data products. The implementation leverages AstraZeneca’s Drug Development Data Platform, which ingests clinical, regulatory, quality, and safety sources and aligns them to controlled vocabularies to produce findable, accessible, interoperable, and reusable datasets.
Integrations were implemented to connect the multi-agent system to company systems, APIs, and the 3DP data products, enabling transparent access to the underlying tables and provenance for returned results. Operational coverage explicitly includes clinical development, regulatory, patient safety, and quality teams, and the platform was scaled into production for more than 1,000 users. The configuration emphasizes domain-aware agents to maintain performance and contextual accuracy for R&D workflows.
Governance and rollout followed a production-ready pathway, moving Development Assistant from concept to production in six months while completing cybersecurity and AI governance checks. The deployment includes built-in guardrails and transparency features that show which data tables were accessed and how answers were generated. AstraZeneca and AWS plan to expand the application beyond clinical trials into other R&D domains, with the current implementation already delivering faster insights and documented cost savings within the constrained scope described.
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Baptist Health | Healthcare | 27000 | $7.0B | United States | Amazon Web Services (AWS) | AWS Bedrock | Generative AI Platforms | 2022 | n/a |
In 2022, Baptist Health implemented AWS Bedrock as its Generative AI Platforms solution, provisioning a centralized generative AI layer to support retrieval augmented generation pipelines. The implementation focused on architecting MCP, A2A, and RAG pipelines that consume AWS Bedrock for model inference and embedding generation, integrating Bedrock inherent embeddings models to produce vector representations for downstream retrieval.
Configuration concentrated on RAG and agentic capabilities, with AWS Bedrock used for model hosting, Amazon Bedrock Data Automation and Amazon Bedrock Knowledge Bases employed for knowledge management, and LangChain integrated for advanced agentic RAG workflows. The design included multimodal RAG techniques, hybrid search approaches, persistent memory patterns, and multi-agent orchestration using LangGraph to coordinate autonomous agent workflows.
Integrations included vector stores and retrieval layers, with vector representations persisted to MongoDB Atlas, Pinecone, and FAISS for similarity search and retrieval. The implementation layered Amazon OpenSearch for traditional and neural search patterns, and CI CD pipelines were automated with GitHub Actions while FastAPI was used to expose inference and orchestration endpoints, enabling DevOps, MLOps, LLMOps, AIOps, and DataOps workflows.
Governance and lifecycle controls emphasized experiment tracking and iteration, utilizing LangSmith to manage RAG experiments and to record agent behaviors and retrieval outcomes. Rollout and operationalization focused on repeatable CI CD workflows and automated build pipelines, with architecture choices oriented toward modular retrieval, agent orchestration, and knowledge base automation within the Generative AI Platforms deployment at Baptist Health.
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BMW | Automotive | 157457 | $165.8B | Germany | Amazon Web Services (AWS) | AWS Bedrock | Generative AI Platforms | 2025 | n/a |
In 2025 BMW deployed AWS Bedrock as a Generative AI Platforms implementation to automate and accelerate root cause analysis for cloud incidents affecting its BMW Connected Company services and a connected fleet of more than 23 million vehicles. The deployment centers on Amazon Bedrock Agents built on the ReAct reasoning and action framework, combining generative AI reasoning with executable tools to replicate engineer workflows for incident diagnosis.
The implementation architecture uses Amazon Bedrock Agents orchestrating a set of Lambda-implemented tools, each mapped to a discrete capability. The Architecture Tool consumes C4 diagrams surfaced via Structurizr to provide component topology and dependency context, the Logs Tool queries CloudWatch Logs Insights for event pattern detection, the Metrics Tool analyzes CloudWatch metrics and alarms for statistical anomalies, and the Infrastructure Tool interrogates AWS CloudTrail for control plane events such as security group and configuration changes. Agents sequence tool invocations iteratively to form and refine hypotheses, and agents present ordered hypotheses to engineers for human-in-the-loop validation.
Integrations are explicit to AWS observability and control plane services, including Amazon CloudWatch, CloudWatch Logs Insights, AWS CloudTrail, and AWS Lambda, with evidence aggregated in a cross account observability setup spanning BMW’s multi regional AWS footprint and some workloads hosted elsewhere. Operational scope includes SRE and engineering teams responsible for connected services, on call incident engineers who interact directly with the agent, and junior engineers who use the agent’s findings to accelerate learning and troubleshooting.
Governance and process changes center on the ReAct agent workflow, which enforces iterative reasoning, targeted tool use to minimize unnecessary queries, and a human-in-the-loop approval model for final remediation steps. The solution moved through a proof of concept where the automated RCA agent identified the correct root cause in 85 percent of test cases and demonstrated significantly lower diagnosis times, reducing investigations that previously could take hours to minutes. AWS Bedrock and its agent tooling are organized for modular extension, enabling BMW to tailor additional diagnostic capabilities as new services and observability sources are onboarded.
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Cox Automotive | Professional Services | 29000 | $23.0B | United States | Amazon Web Services (AWS) | AWS Bedrock | Generative AI Platforms | 2025 | n/a |
In 2025, Cox Automotive deployed AWS Bedrock as part of its Generative AI Platforms strategy, using Bedrock’s AgentCore capabilities to operationalize agentic workflows. Cox Automotive implemented AWS Bedrock to support a spectrum of AI agents, ranging from virtual assistants that improve omnichannel dealer experience to an agentic marketplace that streamlines vehicle discovery and buying, aligning the application with sales and customer engagement business functions.
The implementation centers on AgentCore services within AWS Bedrock, specifically Runtime for secured deployments, Observability for monitoring agent behavior and performance, and Identity for authentication and access control. Configuration emphasis was placed on agent lifecycle controls, secure runtime sandboxes, and telemetry pipelines for observability, enabling product teams to develop, test, and iterate on agent behaviors consistent with Generative AI Platforms capabilities.
Operationally the deployment targets enterprise-wide adoption across product and customer experience teams, integrating agent outputs into dealer-facing omnichannel workflows and marketplace processes for vehicle discovery and purchase. Governance is anchored by Identity and Observability to enforce authentication, traceability, and monitoring during rollout, and the explicit outcome reported is improved team efficiency in developing and testing agents as Cox Automotive scales AI across the enterprise using AWS Bedrock.
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Professional Services | 8000 | $820M | United States | Amazon Web Services (AWS) | AWS Bedrock | Generative AI Platforms | 2025 | n/a |
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Communications | 88826 | $236.7B | Sweden | Amazon Web Services (AWS) | AWS Bedrock | Generative AI Platforms | 2025 | n/a |
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Professional Services | 22500 | $7.5B | Ireland | Amazon Web Services (AWS) | AWS Bedrock | Generative AI Platforms | 2025 | n/a |
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Banking and Financial Services | 1100 | $610M | United States | Amazon Web Services (AWS) | AWS Bedrock | Generative AI Platforms | 2019 | n/a |
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Retail | 40000 | $9.6B | Germany | Amazon Web Services (AWS) | AWS Bedrock | Generative AI Platforms | 2024 | n/a |
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Buyer Intent: Companies Evaluating AWS Bedrock
- Voltik Tech, a China based Manufacturing organization with 242 Employees
- Conexon, a United States based Communications company with 800 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated |
|---|---|---|---|---|---|---|
| Voltik Tech | Manufacturing | 242 | $70M | China | 2026-08-27 | |
| Conexon | Communications | 800 | $90M | United States | 2026-05-02 |