Build AI support agents with a more human touch
With enhanced reasoning and a human-like tone, Claude uses your internal knowledge to take relevant action across systems and tools.
Claude listens carefully, follows instructions precisely, and thinks through complex problems.
Help customers faster with intelligent conversation routing
Deliver personalized responses in any language, across any channel
Cut resolution times and support costs while increasing customer satisfaction
One platform to build, test, and iterate on your AI deployment.
Prompt
Classify all customer support tickets into the most relevant category. Here is the list of categories to choose from:{{CATEGORY_LIST}} Here is the content of the support ticket:{{TICKET_CONTENT}}
What would you like to improve?
Please include a rationale for the classification.
You are an AI assistant specialized in classifying customer support tickets. Your task is to analyze the content of a given ticket and assign it to the most appropriate category from a predefined list. You will also provide reasoning for your classification decision.
First, let's review the available categories:
<category_list>
{{CATEGORY_LIST}}
</category_list>
Now, here is the content of the support ticket you need to classify:
<ticket_content>
{{TICKET_CONTENT}}
</ticket_content>
Please follow these steps to complete the task:
– Carefully read and analyze the ticket content.
– Consider how the content relates to each of the available categories.
– Choose the most appropriate category for the ticket.
– Provide a detailed explanation of your reasoning process.
Use the following structure for your response:
<classification_analysis>
In this section, break down your thought process:
– Quote the most relevant parts of the ticket content.
– List each category and note how it relates to the ticket content.
– For each category, provide arguments for and against classifying the ticket into that category.
– Rank the top 3 most likely categories.
</classification_analysis>
<classification>
<category>Your chosen category goes here</category>
<reasoning>A concise summary of your reasoning for choosing this category</reasoning>
</classification>
Remember to be thorough in your analysis and clear in your explanation. Your goal is to provide an accurate classification with well-supported reasoning.
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“We tested accuracy of the response and the ability of the AI models to have the tone and persona that represented our brand. In both of those cases, we found that Claude models were best for Lyft’s needs.”
“Anthropic provides exceptional support, giving us direct access to expert researchers who help us get the most out of Claude. Our close partnership has been instrumental in pushing output quality for our customers.”
“With Claude, we’re not just automating customer service—we’re elevating it to truly human quality. This lets support teams think more strategically about customer experience and what makes interactions genuinely valuable.”
“Claude performed so well that we’re reevaluating our entire model infrastructure. The reasoning capabilities are significantly better, and the conversational tone feels much more natural even out of the box.”
“We think Claude will help Coinbase build solutions for different customer segments and bring a billion customers to the crypto economy.”
“Businesses will use generative AI, Q included, to tackle ambiguous and highly-fluid self-service use cases. This enables human agents to focus on complex issues that require expertise, enhancing customer satisfaction and employee development.”
“Claude Sonnet delivers the best accuracy, which is crucial for our highly sensitive use cases like refunds and cancellations.”
“Claude fundamentally changes what’s possible in automated customer care. The ability to have nuanced, context-aware conversations through secure enterprise channels opens up entirely new possibilities for how companies and customers interact.”
“Claude is uniquely skilled at understanding and following intricate, multi-step processes with high accuracy. It can navigate the nuanced business logic of each company’s support processes, while catching potential errors before they happen.”