Cloud provider comparison
Compare cloud provider technology stacks using real source-linked deployments: top AI services, technology breadth, capability patterns, recent activity, and the use cases behind each provider signal.
119
25
224
3
Real AI implementations using Microsoft Azure, Azure AI Foundry, Azure OpenAI, Copilot, Microsoft Fabric, and related services.
88
Indexed Logistics & Supply Chain cases
Technology signals
Real AI implementations using Amazon Web Services, including Bedrock, SageMaker, Amazon Q, and cloud-native AI services.
22
Indexed Logistics & Supply Chain cases
Technology signals
Real AI implementations using Google Cloud, including Gemini, Vertex AI, BigQuery, and enterprise AI services.
8
Indexed Logistics & Supply Chain cases
Technology signals
Real AI implementations using Oracle Cloud Infrastructure, including OCI Generative AI, Select AI, Oracle Digital Assistant, and AI embedded in Fusion Applications.
0
Indexed Logistics & Supply Chain cases
Technology signals
Real AI implementations using IBM watsonx, including watsonx.ai, watsonx Orchestrate, watsonx Assistant, and Granite models.
0
Indexed Logistics & Supply Chain cases
Technology signals
Real AI implementations using Alibaba Cloud, including Model Studio, Qwen (Tongyi Qianwen) models, and Platform for AI (PAI).
1
Indexed Logistics & Supply Chain cases
Technology signals
Top technologies · cases scaled to the leader
Top technologies · cases scaled to the leader
Top technologies · cases scaled to the leader
Top technologies · cases scaled to the leader
Technology readout
Microsoft Azure currently has the largest indexed Logistics & Supply Chain evidence footprint with 88 cases in this comparison.
Microsoft Azure spans 119 sampled technologies, led by Azure AI, Azure.
AWS has the strongest recent signal in the latest sampled evidence with 13 cases from the last 180 days.
Microsoft Azure shows the broadest sampled technology adoption context across 1 industries and 22 countries.
Side-by-side table
| Provider | Indexed cases | Share | Recent | Avg. innovation | Top technologies | Technology breadth | Capability pattern | Top industry |
|---|---|---|---|---|---|---|---|---|
| Microsoft | 88 | 74% | 9 | Not scored | Azure AI, Azure, Power Platform | 119 | Agents, Copilot | Logistics |
| 22 | 18% | 13 | Not scored | Amazon Bedrock, Amazon S3, AWS Lambda | 75 | Agents, RAG | Logistics | |
| GCP | 8 | 7% | 3 | Not scored | Vertex AI, BigQuery, Cloud Run | 30 | Agents, Vision | Logistics |
| 0 | 0% | 0 | Not scored | Not enough evidence | 0 | Not enough evidence | Not enough evidence | |
| 0 | 0% | 0 | Not scored | Not enough evidence | 0 | Not enough evidence | Not enough evidence | |
| Alibaba | 1 | 1% | 0 | Not scored | Alibaba Cloud IaaS, edge computing, IoT | 4 | Not enough evidence | Logistics |
Crawlable comparison pages
Evidence examples
United Express worked with Caylent to build an agentic AI observability solution for its weight-and-balance system.,The system ingests millions of log entries, uses Amazon CloudWatch for near real-time alerting, and uses Amazon Bedrock to support conversational investigation of events and API data.,The goal was to detect anomalies earlier and reduce manual log analysis across regional airline operations.
United Airlines strengthened operational resilience across mission-critical AWS workloads using AWS Unified Operations, integrating AI-driven insights, designated AWS specialists, ServiceNow incident management, and Dynatrace monitoring to accelerate incident detection, escalation, and resolution.
Hapag-Lloyd partnered with HERE Technologies on AWS to transform its Live Position system, delivering AI-powered predictive ETAs updated every 15 minutes across all transportation modes.,The solution combines HERE tracking and geocoding capabilities with near-real-time container positioning, processing location updates from 2 million containers using Amazon Kinesis Data Streams and storing structured relationships in Amazon RDS.,Amazon SageMaker AI is used for machine learning-based ETA prediction and Amazon Bedrock adds generative AI and agent capabilities.
Singapore-based startup TetriXX helps customers save up to millions of dollars per year by eliminating logistics inefficiencies.,With Google Cloud, TetriXX provides an AI platform that turns raw data from transportation and logistics invoices into clear, actionable insights.,Using Vertex AI and the Agent Development Kit, TetriXX rapidly develops new AI features and agents, moving them from R&D to production with ease.,The platform also integrates data from external sources to fully inform agent outputs, ensuring they’re accurate, complete, and ready to drive smarter decision-making.,Internally, the organization uses Gemini 3 Pro, Gemini Gems, and NotebookLM to support competitor analysis, consistent responses across functions, and founder knowledge capture.
Heathrow Airport granted its workforce access to Microsoft Office 365 and used Microsoft Power Apps to enable first-line employees to build low-code apps for operational workflows.,Employees created apps such as a mobile language book, a vehicle security app, and the Safe Not-Safe App to reduce paperwork and data-entry burden.,Heathrow also used Microsoft SharePoint to track app development and held monthly Power Apps super user meetings to collect ideas, share feedback, and support adoption.
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.
CrossTech, a UK transport network inspection company, built an automated AI infrastructure inspection platform called Hubble to analyze video data captured from trains and identify hazards such as overgrown vegetation, signal obstructions, level crossing sighting risks, and track ballast issues.,The company migrated to Google Cloud and built a containerized microservices architecture using Cloud Run and Compute Engine for near-real-time processing and autoscaling, with Vertex AI and Vertex AI Notebooks used to accelerate model development and prototyping.,The article also notes continued experimentation with Gemini Enterprise to automate tasks and streamline internal agentic workflows, and with Firebase Studio to simplify coding.
OPLOG, a technology-driven fulfillment company, built a production-ready business intelligence system using AI agents deployed on Amazon Bedrock AgentCore.,The solution processes business transactions autonomously across sales pipeline management, data quality enforcement, and prospect research, integrating HubSpot, Microsoft Teams, Amazon S3, and Amazon Bedrock Knowledge Bases.
MTR Corporation, Hong Kong's rail operator, used Microsoft 365 Copilot and Microsoft Power Platform to reduce administrative workload and fragmented information across the organization.,The initiative embedded AI into everyday work to support drafting, summarisation, analysis, governed low-code applications, and role-based copilots for both internal and customer-facing workflows.,The company also introduced a virtual service ambassador and a station staff enquiry chatbot to provide passengers and frontline employees with approved information and guidance.
FAQ
Microsoft Azure has the largest indexed Logistics & Supply Chain footprint in this view with 88 matching cases.
AWS shows the strongest recent sampled activity with 13 cases from the last 180 days.
The page compares Microsoft Azure, AWS, and Google Cloud using indexed case totals from the filtered dataset. Industry, country, partner, technology, recent activity, and innovativeness signals are calculated from the latest 90 matching cases per provider.
Use the evidence links on each provider card or open the use case ranking with the same provider and industry filters applied.
