oqoqooqoqo
BlogBook a demo

The experimentation platform for the agentic era

Run agentic workflows in production-like environments.
Define the experiment once, repeat it at scale, measure what changes.

Join waitlist
Lab › Define experiment Agent Browser
TaskRubricLibraryEnv
Live demo · click anywhere to drive

What do you want to test first?

Test agent-facing interfaces

Improve the token, latency, and path efficiency of your MCP servers, skills, CLIs, SDKs, and APIs before agents use them.

Run scalable agent evals

Turn real workflows into repeatable evals across agents, models, and treatments in production-like environments.

Gate releases in CI/CD

Block pull requests that break agent workflows, not just unit tests.

Catch model and dependency drift

Rerun the same workflows on a schedule as models, dependencies, and your product change.

Build a benchmark for your product

Turn your user journeys into a repeatable scorecard for how agents perform on your product.

Optimize model spend

Compare your internal workflows across models to find where cheaper models can replace expensive ones.

Power your agent loop

Add a testing harness with proper rubrics and validators, so each iteration is evaluated consistently before feeding the next loop.

Agents are becoming software’s primary user.Build systems that work for them.

Evaluate agentic workflows the way they actually run

Lab›Define experiment
Agent Browser
workflow: refactor-authtreatment: skill
Agents
Opus · High, Sonnet · High
Treatments
Baseline, + skill
Library
⬡ 12 repos
Environment
cloud
Trials
3
0 runsLaunch

Define any experiment

Choose the workflow, treatment, agents, and configuration. Oqoqo turns it into a repeatable experiment.

Experiments›refactor-auth›Run
Agent Browser
env: production-likeisolatedreproducible
sandbox-01 · trial 1running
sandbox-02 · trial 2running
sandbox-03 · trial 3running
trials0 / 36

Run it in a production-like environment

Execute trials in clean, isolated sandboxes so agents interact with the same setup every time.

Experiments›Baseline vs Skill›refactor-auth
Agent Browser
refactor-authFail
TracesOutputEvals
#1
Instruction
Refactor auth so require() stays deterministic across larger graphs.
#2
Assistant
I’ll inspect the module cache before touching the resolver.
#3
Tool · bash
✓ read auth.ts · ✓ grep usages
#4
Tool · fs.edit
✗ edit auth.ts — TypeError: cannot read ‘config’

Capture the full trajectory

Record tool calls, commands, tokens, outputs, and the exact step where the agent got stuck.

Experiments›refactor-auth›Compare
Agent Browser
Metrics
Steps
0
Tokens
0k
Cost
$0.00
Duration
0m 00s
Tool calls
0
Tool calls13
bash30.8%
browser.click30.8%
fs.read23.1%
search15.3%

Measure the effect

Compare success, latency, token use, and frictions across runs. Ask questions grounded in the trace when you need the why.

Automations›refactor-auth›Loop
Agent Browser
improve → agent-facing interface
+ workflow updated
iteration 2Re-run →
on: pull_request…
schedule: nightly…

Feed the next loop

Use the results to improve the agent-facing interface or workflow, then rerun automatically, on a schedule, or in CI/CD.

Frequently askedquestions

Yes. You get up to 100 runs for free.

A few minutes. Pick one of our templates or define your own experiment, then configure the environment however you like.

You can, and you should. Oqoqo turns that useful dogfood step into repeatable testing across controlled tasks, agents, versions, environments, and product changes.

A sandbox just runs the agent. Oqoqo runs the whole experiment around it: production-like environments with real repos, data, and files, controlled variables across agents, models, and versions, and full traces, metrics, diffs of what changed, and evals on every run. You get repeatable, comparable results at scale instead of a one-off script you have to build and maintain.

We start with Claude Code and Codex, and are expanding coverage to Cursor, GitHub Copilot, Antigravity, and OpenCode. You can run different models and effort levels per agent.

SDKs, APIs, CLIs, MCP servers, skills, and more. Anything an agent would touch can be tested and evaluated.

Yes. You define a basic rubric and our system rewrites it to follow best practices — an out-of-the-box capability that delivers high-grade eval results at scale.

Yes. Each run records files read, commands issued, tool calls made, errors hit, and the point where the agent recovered or stopped. Traces live in the workspace for every published run. A reasoning hook also captures the “why” behind each agent decision throughout the run.

Run your first agent experiment

Start with a template or define your own. Test agentic workflows in production-like environments, measure the effect, and feed your next iteration.

Join waitlist