AI case study

Safe conversational AI

by
Amazon
Context

Amazon integrated Anthropic’s Claude models in Alexa+ to power its digital assistant, enhancing conversational reliability and advanced jailbreaking resistance. The integration was implemented via Amazon Bedrock with a close collaboration between Amazon and Anthropic teams. This deployment improved the core business process of delivering secure and trustworthy AI-driven interactions to consumers and businesses.

Results
Results not reported in the source
Published
February 26, 2025
Agent type
Customer Agents
AI provider
Anthropic
Models/tools
Not disclosed
ICE score
567
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
7

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

97

solutions powered by

Anthropic

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
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
Use case
Personalized student support
Context

Pensieve integrated Anthropic's Claude models (Claude 3.5 Sonnet and Claude 3.7 Sonnet) to build AI teaching assistants that automate grading and provide 24/7 personalized tutoring. The system clusters student submissions to calibrate grading rubrics and transforms static PDFs into interactive worksheets while enforcing instructor-controlled policies. This integration streamlines course management workflows and enhances real‐time classroom analytics.

Models/tools
...
2
Explore AI providers

279

AI use cases in

North America

See All
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
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
Use case
Personalized student support
Context

Pensieve integrated Anthropic's Claude models (Claude 3.5 Sonnet and Claude 3.7 Sonnet) to build AI teaching assistants that automate grading and provide 24/7 personalized tutoring. The system clusters student submissions to calibrate grading rubrics and transforms static PDFs into interactive worksheets while enforcing instructor-controlled policies. This integration streamlines course management workflows and enhances real‐time classroom analytics.

Models/tools
...
2
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Thoughts & ideas