Introducing AINET: simulate how AI agents choose and use your API
AI agents now pick APIs and MCP servers on their users' behalf. AINET simulates that journey end to end and tells you what to fix.
By AINET Team
AINET simulates how AI agents such as Muse, Grok Bot, Instinct and Dot find, choose, call and pay for your API or MCP server. It shows where they drop off and ranks the fixes that turn them into paid usage.
Why we built AINET
A growing share of API traffic no longer starts with a developer reading your docs. It starts with an agent that was asked to get something done: fetch a live price, swap a stablecoin, book a meeting, reconcile a wallet. The agent searches, compares a few options, reads just enough documentation to make a call, and moves on.
If your API is hard to find, hard to compare or hard to call, the agent quietly picks someone else. You never see the lost request. It doesn't show up in your analytics, your funnel or your churn report.
We built AINET to make that invisible journey visible.
What AINET does
AINET runs your product through the same journey an agent takes, in four steps:
- Map tasks. We map the tasks agents are actually asked to do in your category, and the personas behind them.
- Simulate agents. We run leading agents on those tasks end to end, from the first search to the final payment.
- Benchmark rivals. We show which API or MCP each agent picks instead of you, and what changed when it switched.
- Ship fixes, then retest. You get concrete changes to your docs,
llms.txt, MCP tools and pricing pages, ranked by expected impact, and a retest under the same conditions.
You can see the loop in action on the homepage.
What you can measure
- Discovery. Does your API or MCP surface for the task the user asked for, not just for your brand name?
- Selection. When an agent compares options, how often does it pick you, and who wins when it doesn't?
- Execution and payment. Can the agent call you correctly, recover from errors and complete payment, including machine payments like x402?
- Task completion. Does the user end up with a finished result?
Who it's for
AINET is built for teams whose growth depends on being chosen by agents: data and infrastructure APIs, payment and execution APIs, and anyone shipping an MCP server. Crypto and fintech APIs feel this first, because their users already work through bots and agents.
Bring your own stack
If you already use a GEO platform to track what chatbots say about you, keep it. AINET works alongside it, and you can run simulations on your own ChatGPT, Claude or Gemini subscription. Read more about bringing your own stack, or why we think GEO is now table stakes.
Get started
We're onboarding teams now. Request a trial and we'll run a free agent report on one of your API tasks.