Stack
Kameleoon
You describe the experiment in a sentence and it builds it. The most AI-native option in this row, and a European company if that matters to you.
When does Kameleoon fit?
Takes the same slot as VWO, AB Tasty or Optimizely. The reason to pick it is the prompt-based setup and how much of the product an assistant can reach, not the feature list. Kai, the assistant built into the product, carries the same tool set as the MCP server without a connection step, so the AI route works before you have wired anything up.
Can an AI assistant drive Kameleoon?
Yes, and it can change things rather than only report on them. Creates experiments, goals, segments, traffic splits and flags per environment, and one lifecycle tool covers start, pause, resume, stop and delete. It reads results for every attached goal with conversion rates, significance and confidence intervals, and calls a winner on the primary goal only. It cannot write a variation's code into a running test - transpose_winning_experiment runs the other way, handing the winning variation's code and implementation instructions to the assistant so the win is rebuilt natively in your own repo behind a flag it creates.
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