+
Amazon Bedrock · Amazon SageMakerIndustrial Vehicle Intelligent Platform
An AWS-based AI and IoT solution using LLMs and agents to power predictive maintenance and data-driven operations across 5,000+ industrial vehicles
Hangcha Group Co., Ltd.
As the fleet kept growing, after-sales operations came under mounting pressure — without digital transformation, Hangcha risked losing its lead in an AI-driven industry
Weak Data Analytics
Massive fleet operation data sat unused, leaving business decisions without solid data support or a clear path to optimization.
No Predictive Maintenance
No way to intervene before equipment failures occurred — reactive repair was the norm, always one step behind.
Slow After-Sales Response
Lengthy service chains kept increasing unplanned downtime while maintenance costs stayed stubbornly high.
Growing Business Risk
Operational bottlenecks directly threatened customer satisfaction and market competitiveness.
A scalable intelligent operations engine deeply integrating AWS cloud services with AI/ML platforms, deployed securely across thousands of industrial assets
Core AWS Services
Five AWS services centered on Bedrock form the platform's AI, compute, storage, and data foundation
Generative AI & Agents
LLM inference and agent orchestration driving knowledge-graph diagnostics, smart scheduling, and natural-language interaction
Model Training
Supports the platform by training custom maintenance prediction models over the fleet-wide data pipeline
Elastic Compute
Scalable compute foundation for the operations engine and partner API integrations
Object Storage
Manages OTA upgrade packages and multimodal data inputs, hosting the fleet-wide data lake
Relational Database
Stores fleet operations and after-sales data, powering real-time analytical queries
Platform Capabilities
A complete edge-to-cloud data pipeline that turns every vehicle into a node of the intelligent operations network
Data Pipeline & Prediction Models
A fleet-wide data pipeline supporting real-time analytics and predictive maintenance; custom SageMaker models reached 92% prediction accuracy.
OTA & Multimodal Management
S3-based management of OTA upgrade packages and multimodal data, completing remote upgrades for 5,000+ vehicles within 3 months.
Edge Computing
Local data pre-processing at edge nodes significantly reduces latency and cloud load, keeping field operations responsive.
Knowledge-Graph Diagnostics & APIs
Bedrock-powered knowledge-graph fault diagnostics plus deep API integrations with partner systems form an open service ecosystem.
Rapid deployment delivered measurable operational improvements, validating platform effectiveness and ROI
Average Equipment Availability
85%, with frequent unplanned downtime
92%
90%, a marked availability gain
Annual Repair Cost Share of OpEx
12%, driven by reactive repairs
9%
10%, with a steadily improving cost structure
Custom models covering critical components fleet-wide
Combined gains from smart scheduling and data-driven decisions
Rapid rollout at scale, proving strong ROI
Generative AI components delivered 25% of the solution's core capabilities from 30% of the spend, with pay-as-you-go pricing cutting technical complexity
About $31,700 on Bedrock and SageMaker — 30% of total project spend
Supporting core solution capabilities such as prediction models and smart scheduling
Integrated services cut overall operating costs by 35% versus legacy systems
Let AI Drive Your Fleet Operations
Learn how AI-Driven can build your industrial vehicle intelligent platform on AWS