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OpenAI

Build every step of agents on one platform

Ship production-ready agents faster and more reliably across your products and organization.

Diagram segment showing a simple agent workflow against a blue and orange gradient background. The flow connects three nodes: a green ‘Start’ button, a blue ‘Categorize Agent’ step, and a tan branching icon representing the next action.

Leading organizations build agents with OpenAI

“Agent Builder transformed what took months of orchestration, custom code, and manual optimization into hours—getting an agent live in two sprints instead of two quarters.”

70%

reduction in iteration cycles

40%

faster agent evaluation timelines

2 weeks

of custom front-end UI work saved when building an agent

30%

increased agent accuracy with evals

75%

less time to develop agentic workflows

The complete platform for agent development

AgentKit gives you the tools to build agentic workflows, deploy UI, and optimize performance, fast and reliably.

Three-tier diagram illustrating the workflow of AI system development. The top section, labeled ‘Build,’ includes four boxes: Models, Tools, Prompts, and Guardrails. The middle section, labeled ‘Deploy,’ contains one box titled User Interface. The bottom section, labeled ‘Optimize,’ shows three connected boxes—Optimization, Orchestration, and Observability—with a dotted arrow looping back from Observability to Optimization.

Build with Agent Builder and the Agents SDK

Design agents on a visual-first canvas or in a code-first environment—both powered by the Responses API.

Flow diagram showing a simple automation built in the Agent Builder. The sequence starts with a green ‘Start’ node, followed by an orange ‘Customer lookup’ connector, which branches into two outcomes: a blue ‘Analyze bills’ node and a grayed-out ‘No past bills’ node.
Visual-first
Agent Builder

Build workflows visually with drag-and-drop nodes, versioning, and guardrails. Use templates or start from a blank canvas.

Code snippet displayed on a gradient background showing a simple Python example using the Agents SDK. The script imports Agent and Runner, defines an asynchronous function that creates an agent named ‘Assistant’ with instructions to respond only in haikus, runs the agent with a recursion prompt, and prints the final output.
Code-first
Agents SDK

Build agents in Node, Python, or Go with a type-safe library that’s 4× faster than manual prompt-and-tool setups.

Built-in tools for smarter tasks

Our models use tools to bring in relevant context—making responses more accurate and helpful.

Web search

Access up-to-date and clearly cited answers from the Internet.

File search

Retrieve relevant knowledge from internal files.

Image generation

Create images from natural language and iterate with high-fidelity.

Code interpreter

Run Python code iteratively with high accuracy.

Computer use

Build computer-using agents that complete browser-related tasks on your behalf.

Connectors and MCP servers

Connect to popular business apps and MCP servers to pull internal and external context into our models.

Deploy with ChatKit

Launch fully integrated chat experiences with drag-and-drop customization.

Ramp’s buyer agent, powered by AgentKit.

Optimize with Evals

New tools help you test and refine agents with more precision and efficiency.

Icon representing trending upwards

Evals

Run evals(opens in a new window) and set custom graders(opens in a new window) to determine whether the agent is performing to your expectations on your specific use case.

Icon representing a tuning fork

Prompt optimization

Improve prompts through automatic prompt optimization(opens in a new window) based on the results of your eval runs.

Icon representing grading

Trace grading

Set the pass criteria once and let LLM graders evaluate the last 100—or 1,000—executions of your workflow.