AI case study

Personalized fitness at scale

by
Technogym
Context

Technogym integrated Google Cloud’s generative AI services including Gemini, Vertex AI, and BigQuery to analyze vast amounts of user data stored in Cloud Storage, enabling the creation of hyper-personalized workout, nutrition, sleep, and mindfulness programs. The AI-powered Technogym Coach is embedded into their digital ecosystem, streamlining fitness planning and enhancing customer engagement across both physical and digital channels.

Results

Increased user engagement and improved fitness outcomes

Results not reported in the source
Industry
Healthcare
Region
Europe
Published
October 11, 2024
Agent type
Customer 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

75

AI use cases in

Healthcare

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Ontada

Healthcare
Data Agents
Quick win
Use case
Faster oncology data extraction
Context

Ontada leveraged Microsoft’s Azure OpenAI Service Batch API and Azure AI Foundry to build its ON.Genuity platform, which processes 150 million unstructured oncology documents to automatically extract nearly 100 critical data elements across 39 cancer types. They integrated the new platform with their structured iKnowMed system using Azure Databricks for data ingestion and Azure Document Intelligence for text extraction, transforming manual chart review processes into an automated workflow that supports clinical decision-making and life science product development.

DrumBeat.ai

Healthcare
Use case
Limited specialist access
Context

DrumBeat.ai developed an AI-driven diagnostic tool integrated with an ear camera that analyzes digital images of patients’ ears to provide instant identification of abnormalities such as perforated eardrums and signs of chronic otitis media. The system was implemented by training the model on over 10,000 images from 4,000 children across 100 indigenous communities, enabling non-specialists in remote areas to perform assessments and facilitate timely referrals.

Models/tools
No items found.
...

Dynamic Health Systems

Healthcare
Use case
Lower clinical workload
Context

Dynamic Health Systems built its VitruCare365® platform on Microsoft Cloud for Healthcare by integrating Microsoft Azure, FHIR, Dynamics 365, and Azure OpenAI Service to deliver personalized patient apps and AI-powered chatbots. They deployed a retrieval augmented generation technique with custom RAG Flag technology and integrated the solution within Microsoft 365 for telemedicine consultations, appointment scheduling, and motivational care planning. This comprehensive integration automated patient engagement and care plan management, streamlining clinical workflows.

Explore industries

166

companies using

Customer Agents

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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
Rigid support workflows
Context

Zendesk integrated OpenAI's models to create adaptive AI service agents that autonomously manage customer conversations and execute resolution tasks. They implemented a multi-agent architecture featuring task identification, conversational RAG, procedure compilation, and procedure execution agents integrated with existing support workflows through API calls and natural language procedure definitions, while providing real-time chain-of-thought visibility. This solution transitions from traditional intent-based bots to a hybrid model of scripted and generative reasoning, streamlining customer service processes.

Models/tools
...
2
Use case
Faster finance/legal research
Context

Hebbia built Matrix, a multi-agent AI platform that orchestrates OpenAI models including o3‑mini, o1, and GPT‑4o to automate complex financial and legal research tasks. The platform decomposes intricate queries into structured analytical steps and integrates modules like OCR, hallucination validation, and artifact generation to process complete documents, creating an infinite effective context window. This solution streamlines due diligence, contract review, and market research workflows, drastically reducing manual processing time.

Models/tools
...
3
Explore agents

255

solutions powered by

Google

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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

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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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