AI case study

Faster customer onboarding

by
Plenitude
Context

Plenitude harnessed Google Cloud’s OCR and PaLM models alongside Document AI to automatically extract data from energy bills and verify customer IDs. They implemented a cloud-based workflow using Vertex AI Platform to integrate with its registration systems and automate identity checks, effectively streamlining customer onboarding and fraud prevention processes.

Results

Faster onboarding, increased registration completion, reduced fraud, and significant time savings in ID verification.

Results not reported in the source
Region
Europe
Published
October 11, 2024
Agent type
Data Agents
AI provider
Google
ICE score
448
The ICE framework in this database provides a quick way to assess the feasibility and potential impact of AI use cases, with higher scores signaling more actionable opportunities.

Impact: Potential benefits to the business.

Confidence: Likelihood of achieving expected results.

Ease: Simplicity of implementation in terms of resources and time.

ICE Score: Calculated by multiplying the component scores.

Note:
Each score is AI-generated based on available data and should be viewed merely as a general guideline for deeper exploration of the use cases.
Impact
8
Confidence
8
Ease
7

17

AI use cases in

Energy & Sustainability

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AES

Energy & Sustainability
Use case
Faster safety audits
Context

AES deployed generative AI agents built on Vertex AI and Anthropic’s Claude models to overhaul its health and safety audit processes. They connected Claude via API calls within the Vertex AI environment, addressing security through configured service accounts and leveraging Vertex AI Model Garden for simplified deployment. This automation streamlined document reviews for large, multilingual audit files, significantly reducing manual labor.

Models/tools

Emirates Global Aluminium

Energy & Sustainability
Data Agents
Quick win
Use case
Scalable hybrid computing
Context

Implemented a hybrid cloud architecture by moving one-third of its servers to Azure public cloud and another third to Azure Local for edge capabilities, managed via Azure Arc to seamlessly integrate on-premises and cloud environments for advanced industrial AI use cases.

AES

Energy & Sustainability
Data Agents
Quick win
Use case
Scaling renewable energy asset management
Context

AES uses Claude on Google Cloud’s Vertex AI to automate their safety audit process, employing a multi-agent system to analyze documents, break down tasks, and generate reports. This system processes hundreds of pages, evaluates compliance, and produces detailed audit reports in about an hour.

Models/tools
Explore industries

149

companies using

Data Agents

See All
Use case
Automated job title classification
Context

Aura Intelligence integrated Anthropic's Claude via Amazon Bedrock into its data pipeline to automatically classify over 200 million job titles and industry pairings from multi-language data, replacing manual lookups and fuzzy matching. They fine-tuned foundation models on proprietary datasets and leveraged AWS infrastructure, including SageMaker and prompt management, to automate QA, report generation, anomaly detection, and real-time hiring trend analysis.

Models/tools
...
2
Use case
Efficient engineering team management
Context

LaunchNotes leverages Claude in Amazon Bedrock in their product 'Graph' to transform engineering data into actionable insights. Graph functions as an ETL platform with Claude managing data pipelines, helping engineering managers understand development metrics, reduce incident identification time, automate updates, and generate customized release notes and technical documentation.

Models/tools
...
2
Use case
Faster data insights
Context

Snowflake integrated Anthropic's Claude into their platform to enable natural language queries on complex databases, allowing customers to extract insights without SQL expertise while maintaining security and governance.

Models/tools
...
2
Explore agents

255

solutions powered by

Google

See All
Use case
Fast registration & safety
Context

704 Apps implemented an AI solution using Vertex AI and Gemini 1.5 Pro to automate and accelerate driver identity verification and safety monitoring. They integrated these AI models into their existing cloud infrastructure built on Firebase and Google Kubernetes Engine, centralizing real-time data for document validation and audio sentiment analysis. The system alerts the central monitoring team when risk-related language is detected, streamlining operational decision-making and enhancing security.

Models/tools
...
2
Use case
AI integration on mobile
Context

OPPO integrated Google Cloud’s Vertex AI, AutoML, and Gemini large language model into its mobile devices to automate user feedback analysis, power AI Recording Summary features, and enable AI Toolbox functionalities such as AI Writer and AI Reply. They re-engineered their hardware platform, operating system, and third-party ecosystem to embed AI agents that optimize power consumption and reduce computing latency, streamlining mobile development workflows and enhancing user experience.

Models/tools
...
4
Use case
Personalized post-click landing
Context

Dataïads built an AI-powered “Post-Click Experience” system that automatically generates personalized landing pages by analyzing user context such as ad origin, product type, and behavior. The solution is implemented by integrating API access from Google Ads with Google Cloud managed services (Cloud Run and BigQuery) for automated scaling and controlled cost management, while planning to incorporate Vertex AI for further optimization. This implementation directly enhances ad campaign management and improves ecommerce conversion processes.

Models/tools
...
1
Explore AI providers

153

AI use cases in

Europe

See All
Use case
Automated customer support
Context

Tidio integrated Anthropic’s Claude model to develop their Lyro AI agent, automating customer support interactions across both live chat and email channels. They implemented a network of specialized AI agents for conversation rating, summarization, and a dynamic routing system that selects the optimal API between native Anthropic API and Google Cloud Vertex AI based on performance metrics, streamlining support workflows and enabling personalized product recommendations.

Models/tools
...
2
Use case
Multilingual reading difficulties
Context

The school deployed Microsoft Reading Progress and Microsoft Immersive Reader, two AI-powered apps integrated within Microsoft Teams, to support individualized learning. The tools record reading sessions, provide real-time feedback on pronunciation and errors, and translate texts to enable comprehension across multiple languages. This setup streamlines classroom instruction, personalizes student learning, and reduces teacher workload.

Models/tools
...
2
Use case
Personalized post-click landing
Context

Dataïads built an AI-powered “Post-Click Experience” system that automatically generates personalized landing pages by analyzing user context such as ad origin, product type, and behavior. The solution is implemented by integrating API access from Google Ads with Google Cloud managed services (Cloud Run and BigQuery) for automated scaling and controlled cost management, while planning to incorporate Vertex AI for further optimization. This implementation directly enhances ad campaign management and improves ecommerce conversion processes.

Models/tools
...
1
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Thoughts & ideas