AI case study

Simplified perishable ordering

by
Fortenova Group
Context

Fortenova Group leveraged Vertex AI to build an AI forecasting tool that analyzes historical order data, current inventory levels, and seasonal trends to predict daily demand for perishable products such as fruits and vegetables. The tool was integrated into the grocery store ordering workflow by automating model training, monitoring, and third-party connectivity, enabling store managers to quickly determine optimal order amounts and reduce food waste.

Results

Reduced food waste and streamlined ordering

Results not reported in the source
Region
Europe
Published
September 6, 2024
Agent type
Employee Agents
AI provider
Google
Models/tools
Not disclosed
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

28

AI use cases in

Consumer Goods

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Mercari

Consumer Goods
Use case
Simplified listing process
Context

Mercari integrated OpenAI’s API with a multi-model approach to optimize product listings. Initially, GPT‑4 analyzed top listings offline while GPT‑3.5 Turbo provided real-time suggestions for active listings. Later, they shifted to GPT‑4o mini to automatically generate complete titles, descriptions, and category suggestions from uploaded photos, streamlining the seller listing workflow.

Models/tools

ASOS

Consumer Goods
Use case
Personalized product discovery
Context

ASOS integrated Azure OpenAI Service and Azure AI prompt flow to build an AI-powered natural language interface on its website and mobile app for personalized product recommendations. They implemented the solution by connecting their existing microservices with these AI tools, streamlining rapid prototyping and integrating external trend data along with internal expertise to curate tailored selections that enhance customer engagement. The solution seamlessly integrates into ASOS’s digital processes.

Pets at Home

Consumer Goods
Use case
Faster fraud detection
Context

Pets at Home built an AI agent using Microsoft Copilot Studio integrated into its unified Azure data platform that consolidates disparate systems from its retail stores, online channel, veterinary clinics, and grooming services. This agent empowers the retail fraud detection team by rapidly scanning extensive transaction data to identify anomalies such as duplicate images in fraudulent claims, thereby streamlining fraud investigations. The implementation required minimal coding and seamlessly connected existing systems while ensuring strict data privacy within the company ecosystem.

Models/tools
Explore industries

321

companies using

Employee Agents

See All
Use case
Fast content creation
Context

Cox Automotive integrated Claude via Amazon Bedrock into its portfolio by first creating a sandbox environment to evaluate performance metrics and then selecting Claude 3.5 Sonnet for complex tasks and Claude 3.5 Haiku for high-volume content generation. They automated personalized dealer-consumer communications, generated engaging vehicle listing descriptions, and produced SEO-optimized blog posts, while also streamlining internal data governance through automated metadata generation. This integration optimized operational efficiency across marketing and internal data processes.

Models/tools
...
2
Use case
Reduce report writing burden
Context

Quillit integrated Anthropic’s Claude to automate qualitative research tasks by summarizing interview transcripts, generating contextual citations, and threading conversation data into comprehensive reports. They implemented the AI tool into their existing research workflow within three months, streamlining report writing, transcription, and analysis while ensuring data security and high precision.

Models/tools
...
2
Use case
Faster retail transformation
Context

TCS partnered with Google Cloud to integrate advanced AI and generative AI capabilities into retail service offerings. They launched the Google Cloud Gemini Experience Center at their Retail Innovation Lab in Chennai, enabling retail clients to ideate, prototype, and co-develop tailored AI solutions that optimize supply chain, warehouse receiving, customer insights, and content creation. This approach automated processes using tools like Vertex AI Vision for warehouse receiving and leveraged Vertex AI with Gemini 1.5 Pro and speech-to-text to transform service centers.

Models/tools
...
4
Explore agents

263

solutions powered by

Google

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Use case
Faster retail transformation
Context

TCS partnered with Google Cloud to integrate advanced AI and generative AI capabilities into retail service offerings. They launched the Google Cloud Gemini Experience Center at their Retail Innovation Lab in Chennai, enabling retail clients to ideate, prototype, and co-develop tailored AI solutions that optimize supply chain, warehouse receiving, customer insights, and content creation. This approach automated processes using tools like Vertex AI Vision for warehouse receiving and leveraged Vertex AI with Gemini 1.5 Pro and speech-to-text to transform service centers.

Models/tools
...
4
Use case
Faster research reports
Context

Deutsche Bank developed DB Lumina, an AI-powered research agent built on Gemini and Vertex AI through a partnership with Google Cloud. The solution automates the creation of financial research reports by rapidly condensing extensive market data—such as converting a 400-page report into a three-page summary—thereby streamlining analysis workflows while maintaining rigorous data privacy standards.

Models/tools
...
2
Use case
Secure on-premises AI
Context

NVIDIA partnered with Google Cloud to enable on-premises agentic AI by integrating Google Gemini models with NVIDIA Blackwell platforms and Confidential Computing, ensuring data sovereignty and regulatory compliance for sensitive enterprise operations. The solution further optimizes AI inference and observability by deploying a GKE Inference Gateway alongside NVIDIA Triton Inference Server, NVIDIA NeMo Guardrails, and NVIDIA Dynamo to enhance secure routing and load balancing for enterprise workloads.

Models/tools
...
7
Explore AI providers

159

AI use cases in

Europe

See All
Use case
Faster research reports
Context

Deutsche Bank developed DB Lumina, an AI-powered research agent built on Gemini and Vertex AI through a partnership with Google Cloud. The solution automates the creation of financial research reports by rapidly condensing extensive market data—such as converting a 400-page report into a three-page summary—thereby streamlining analysis workflows while maintaining rigorous data privacy standards.

Models/tools
...
2
Use case
Optimized CX workflows
Context

Capgemini partnered with Google Cloud to develop industry-specific agentic AI solutions that automate customer request handling across multiple channels such as web, social, and phone. The implementation integrates Google Agentspace, Customer Engagement Suite, and Agent2Agent interoperability protocol into existing customer service infrastructures to enhance personalized support, call routing, and workflow automation. This advanced solution transforms customer experience by streamlining communications and enabling proactive engagement.

Models/tools
...
3
Use case
Scalable contract detection
Context

wealthAPI implemented a next‐gen contract detection solution by integrating DataStax Astra DB on Google Cloud and leveraging Google Gemini models for AI‐powered analysis. They deployed DataStax’s vector search and real‐time insights capabilities to scale contract detection across millions of users in less than three months, streamlining wealth management workflows by dramatically reducing response times and efficiently handling massive data volumes.

Models/tools
...
1
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