Claude Platform

Build frontier agents on the Claude Platform

Frontier models, harnesses, context management, and infrastructure designed to work together.

Save 50% with batch processing. Learn more (opens in new tab)

Fable 5.1

Next generation intelligence for long-running agents

Prompt caching
Read
$0.25 / MTok
Write
$12.50 / MTok
Input
$10 / MTok
Output
$50 / MTok

Model use cases:

  • Multi-day autonomous projects
  • Expert-level work for frontier research
Explore Fable (opens in new tab)

Opus 5.5

Daily driver for agentic coding and enterprise work

Prompt caching
Read
$0.20 / MTok
Write
$5 / MTok
Input
$4 / MTok
Output
$20 / MTok

Model use cases:

  • Long-horizon coding and large migrations
  • Multi-step agents across enterprise tools and data
Explore Opus (opens in new tab)

Sonnet 5.5

High-performance model for coding and agents

Prompt caching
Read
$0.20 / MTok
Write
$2.50 / MTok
Input
$2 / MTok
Output
$10 / MTok

Model use cases:

  • Everyday coding and developer loops
  • Customer-facing agents and multi-tool workflows at scale
Explore Sonnet (opens in new tab)

Haiku 4.5

Fastest, most cost-effective model

Prompt caching
Read
$0.10 / MTok
Write
$1.25 / MTok
Input
$1 / MTok
Output
$5 / MTok

Model use cases:

  • Real-time, latency-sensitive product experiences
  • Sub-agents inside larger multi-model systems
Explore Haiku (opens in new tab)

For workloads that need to run in the US, US-only inference is available at 1.1x pricing for input and output tokens. Learn more.

Get up to 2.5x faster speeds with fast mode for Opus 5.5 at 2x standard pricing. Learn more.

Prompt caching pricing reflects 5-minute TTL. Learn about extended prompt caching.

Access Claude’s frontier models through the Messages API to build with full control and customization.

Code execution

Run Python code, create visualizations, and analyze data in API calls.

Structured outputs

Ensure Claude's responses conform to your JSON schema.

Tool use

Allow Claude to interact with hundreds of external tools and APIs so it can perform a wider range of tasks.

Computer use

Let Claude see and operate a browser or desktop to automate work in applications that have no API.

Citations

Ground responses in source documents.

Files

Upload and reference documents across conversations.

Context window

Run more comprehensive and data-intensive use cases with up to 1 million tokens of context.

Compaction

Automatically summarize older context when approaching token limits.

Context editing

Automatically clear tool calls and results.

Web search and fetch

Bring current data from the web into Claude.

BETA

Build and deploy long-running agents at scale.

BETA

Built-in capabilities for every agent

Multiagent orchestration

Claude delegates to other agents, each with its own independent context window.

Outcomes

Agents iterate against pre-defined exit criteria, grading their own work against a rubric.

Memory tool

Claude reads and writes to memory stores, so every session gets progressively better.

Scheduled deployments

Run agents on a schedule, so recurring work happens without having to trigger a run.

Self-hosted sandboxes

Keep sensitive files, packages, and services in your own infrastructure, or use a managed provider.

Dreaming

Between sessions, Claude reflects on past runs and codifies what it learned as memory.

MCP tunnels

Reach MCP servers in your private network without exposing them to the public internet.

Vaults

Keep secrets out of your agent code. Register a credential once and reuse it across sessions.

Security by design

Credentials stay out of the sandbox, encryption is built in, and state persists automatically.

Observable end to end

Session tracing records what every agent did and why, with built-in analytics to improve agent performance.

Built for Claude

The underlying harness is optimized for Claude. As the model improves, your agents improve with it.

Extend and customize what Claude can do.

Model Context Protocol (MCP)

Connect Claude to your tools and data through the open standard for AI integrations.

Skills

Teach Claude your expertise, procedures, and best practices through pre-built or customizable skills.

Memory stores

Agents remember across sessions, keeping memory files on your infrastructure.

Claude Marketplace

Use your existing Anthropic commitment to pay for Claude-powered solutions from our partners.

Controls and safeguards for your data.

Enterprise Frontier Safeguards

Gives eligible customers the privacy of zero data retention (ZDR) along with state-of-the-art safeguards for detecting misuse.

Residency

On your cloud provider, choose where your data is stored and where requests are processed, with regions in Asia-Pacific, Canada, Europe, and the United States.

Your data stays yours

By default, Anthropic does not use customer data from commercial deployments to train Claude.

Available on all major cloud providers

Build directly on the Claude Platform, with enterprise security and support built in. Or use Claude in the cloud you already use, including Amazon Web Services, Google Cloud, or Microsoft Foundry.

Batch processing

Process large volumes of requests asynchronously and save 50% on costs.

Prompt caching

Give Claude background knowledge and examples to reduce costs by up to 90%.

Effort

Choose how hard Claude works on a task.

Advisor strategy (beta)

Faster, affordable models call more intelligent models to evaluate plans or work to improve performance.

Your command center, with analytics and controls built in.

Build your request

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}}

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.

Build

Prototype prompts, upload skills and files, configure your agents.

Deploy

Run agents on hosted environments with vaults and memory.

Monitor

Track usage, cost, caching, and rate limits by model and by API key.

Manage

Control API keys, members, token limits, and security per workspace.

Build on the Claude Platform

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Claude Platform | Claude by Anthropic