AI case study

Dynamic property filtering

by
Properstar
Context

Properstar integrated Microsoft Azure OpenAI Service to analyze unstructured property descriptions and extract important property features, enabling enriched data for listings. They combined this with Azure AI Search to build a dynamic filtering system that differentiates between mandatory and optional criteria, streamlining the property search process across global markets. The solution further supports robust market analysis and scalability.

Results

40% more data per property; 98% match rate

Results not reported in the source
Region
Europe
Published
December 9, 2024
Agent type
Customer Agents
AI provider
Microsoft
Models/tools
Not disclosed
ICE score
648
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
9
Confidence
9
Ease
8

107

AI use cases in

Software & IT

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Tidio

Software & IT
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

Zendesk

Software & IT
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

Chatbase

Software & IT
Use case
Instant personalized support
Context

Chatbase integrated Anthropic's Claude into its multi-channel customer support platform to automate routine inquiries and deliver instant, personalized support across web chat, WhatsApp, Slack, and Instagram. They implemented the solution by embedding AI agents through APIs that integrate with business systems such as Stripe for order status checks and refund processing, while enabling customizable brand voice and multilingual communication with optional human oversight. This approach streamlined customer service workflows and provided advanced analytics to help teams quickly identify trends and optimize interactions.

Models/tools
...
1
Explore industries

166

companies using

Customer Agents

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
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

226

solutions powered by

Microsoft

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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
Faster customer issue resolution
Context

Vodafone uses Azure OpenAI Service, Azure AI Foundry, Microsoft Copilot, and Azure AI Search to enhance their virtual assistant TOBi and develop SuperAgent to assist customer service agents. TOBi uses conversational AI to handle customer inquiries, while SuperAgent helps agents solve complex problems faster.

Models/tools
...
4
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.

Models/tools
...
4
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