Agent Studio

How it works

From problem to production

Go from idea to production-ready AI agent in six steps. Define, equip, orchestrate, test, inspect, and evaluate — all in one place.

Step 01

Build Agents

Start with the business problem, not the technology. What decision needs to be made? What process needs to run? Agent Studio helps you frame the right scope before writing a single prompt.

  • Map out the task your agent will handle
  • Identify inputs, outputs, and success criteria
  • Choose the right model for the job
Step 02

Memory & Guardrails

Give your agent a clear identity — how it speaks, what it knows, where the boundaries are. System prompts, temperature, safety filters — all configured in one place.

  • Write system prompts that define behavior
  • Set content moderation and output filters
  • Configure model parameters and constraints
Step 03

Connect Tools

An agent that can't act is just a chatbot. Plug in your APIs, databases, and custom functions so your agent can read data, take actions, and interact with real systems.

  • Add API integrations with JSON schemas
  • Connect databases and knowledge bases
  • Build custom tool functions
Step 04

Test Agents

Have a real conversation with your agent before anyone else does. Watch every tool call as it happens. Iterate on prompts until the responses feel right.

  • Live chat with your agent in the browser
  • See tool calls and responses in real time
  • Tweak prompts and re-test instantly
Step 05

Trace & Evaluate

Every LLM call, every token, every cost, every millisecond — recorded in a searchable timeline. Score responses with automated evals and know exactly how your agent performs.

  • Full trace of every decision and tool call
  • Per-token cost breakdowns
  • LLM-as-Judge and human eval scoring
Step 06

Orchestrate

One agent is useful. Multiple agents working together are powerful. Chain agents with branching logic, parallel execution, and human checkpoints to automate entire processes.

  • Chain agents into multi-step pipelines
  • Add conditional logic and routing
  • Set human-in-the-loop checkpoints