AWSEnergyReal-time AnalyticsAI and Machine LearningGenerative AI / LLMIoTCost ReductionCustomer ExperienceProductivity ImprovementRevenue GrowthScalabilitySpeed to Market2025AWSAWS#ff9900EnergyGlobalRecognizing the potential of generative AI, Noodoe aimed to enhance its product line by integrating AI-powered capabilities. Roman Kleinerman, vice president of products at Noodoe, explains, “We envisioned that within a…According to a Harvard Business School study , charging stations in the US typically achieve 78 percent…Feb 17, 20256Real-time AnalyticsAmazon Bedrock · Amazon CloudWatch · Amazon EC202025-02-176
Recognizing the potential of generative AI, Noodoe aimed to enhance its product line by integrating AI-powered capabilities. Roman Kleinerman, vice president of products at Noodoe, explains, “We envisioned that within a couple of months of a station’s launch, our AI solution would gather sufficient data to start recommending optimal pricing models, eliminating the need for manual analysis.” To accelerate time to market, Noodoe sought to integrate the solution into its existing tech stack without reworking its robust cybersecurity infrastructure.
↗According to a Harvard Business School study , charging stations in the US typically achieve 78 percent reliability, meaning one in five chargers are out of service.
↗At the same time, it exceeded market standards by maintaining 98 percent availability.
↗By using Amazon Bedrock alongside AWS services, Noodoe reduced its time to market from months to weeks while cutting costs by 10 percent.
↗Launched three times faster with expert support, the solution led to a 10–25 percent revenue boost per charging station within months of deployment.
Reported impact
Business outcome
Noodoe launched its generative AI solution in November 2024, and within months its customers were reporting significant revenue growth at their charging stations. Kleinerman shares, “We’ve seen revenue increases of 10 to 25 percent depending on the location and number of stations, as customers use our AI solution to optimize pricing strategies.” Operating within a single AWS-based ecosystem means Noodoe’s customers enjoy high levels of reliability and performance. Key reported metrics include Noodoe launched its generative AI solution in November 2024, and within months its customers were reporting significant revenue growth at their charging stations.; According to a Harvard Business School
Cost Reduction
Customer Experience
Productivity Improvement
Revenue Growth
Scalability
Speed to Market
Solution
Noodoe Boosts EV Charging Station Revenues by 10–25% with Generative AI Advisor on Amazon Bedrock Noodoe , a developer of EV charging solutions with integrated AI capabilities, sought to enhance its product line by leveraging generative AI to optimize pricing strategies for EV charging stations. By analyzing usage data, the AI-driven solution recommends the best pricing models to maximize revenue and improve station utilization. To power this, Noodoe chose Amazon Web Services (AWS), ensuring seamless integration with its existing infrastructure while maintaining security and efficiency. Launched three times faster with expert support, the solution led to a 10–25 percent revenue boost per charging station within months of deployment. At the same time, it exceeded market standards by maintaining 98 percent availability. Source data enters the Noodoe workflow through its application services, stored or indexed in Amazon S3, processed with Amazon Bedrock, Amazon EC2, Anthropic Claude 3.
Data flow
Source data enters the Noodoe workflow through its application services, stored or indexed in Amazon S3, processed with Amazon Bedrock, Amazon EC2, Anthropic Claude 3.
Solution architecture
5 components · 3 layers
Compute
Amazon BedrockHosts the foundation models and inference APIs that power the generative AI features.
Amazon EC2Provides configurable compute capacity for application, training, or inference workloads.
Anthropic Claude 3Serves as the primary large language model for generation, analysis, or reasoning tasks.
Storage
Amazon S3Stores raw, intermediate, or curated files and datasets.
Governance
Amazon CloudWatchCollects operational telemetry and monitoring signals from the workload.
Architecture clues
At the same time, it exceeded market standards by maintaining 98 percent availability.
Evidence from the source
According to a Harvard Business School study , charging stations in the US typically achieve 78 percent reliability, meaning one in five chargers are out of service.
At the same time, it exceeded market standards by maintaining 98 percent availability.
By using Amazon Bedrock alongside AWS services, Noodoe reduced its time to market from months to weeks while cutting costs by 10 percent.
Launched three times faster with expert support, the solution led to a 10–25 percent revenue boost per charging station within months of deployment.
Noodoe launched its generative AI solution in November 2024, and within months its customers were reporting significant revenue growth at their charging stations.
Recognizing the potential of generative AI, Noodoe aimed to enhance its product line by integrating AI-powered capabilities. Roman Kleinerman, vice president of products at Noodoe, explains, “We envisioned that within a couple of months of
Review how this reference was scored and trace each normalized claim back to its documented source.
01
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value95/100
Problem clarity20/20
Measures whether the customer's operational problem is specific enough to compare.
Implementation depth20/25
Rewards named components, data flow, integrations, and architecture detail.
Outcome specificity20/20
Measures whether the reported benefit is concrete rather than a generic claim.
Quantified impact25/25
3 metrics describe measurable impact.
Deployment scale10/10
Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
Source authority20/25
The main evidence is an official vendor-published customer story.
Claim traceability21/25
10 of 12 key fields link to a named source.
Direct evidence20/20
6 direct source quotes retained.
Date provenance8/10
The publication date comes from publisher-controlled metadata.
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