Choose what to investigate
Bring your prompts or get help creating them. Review and edit the set with your agent, then save a version to run across the models you choose.
See beyond
one model’s answer.
Run your prompts across multiple AI models, with or without web search. Collect their answers, then use your AI agent to investigate which recommendations repeat, where answers differ, and what alternatives appear.
Run Any Model handles execution and saves each answer, transcript and cost.
Join the private beta
Join the waitlist for access. Connect your AI agent through MCP.
Choose your prompts, models and budget.
Does your brand make the shortlist?
Twelve buying prompts. Three models. With and without web search.
“Which project management tools work well for a small design studio?”
One prompt from an example set you could bring or create with your agent.
- company mentioned
- company not mentioned
- not measured
Run prompts your buyers might use. Have your agent inspect which brands each model recommends, the reasons it gives, and when your company appears or is absent.
Illustrative patterns, not live findings. Each square is one prompt on one model in one mode.
Which options are you overlooking?
Twelve niche prompts. Three models. With and without web search.
“Which small, independent hotels in Madison, Wisconsin, are good for a quiet working week?”
One prompt from an example set you could bring or create with your agent.
- niche option surfaced
- niche option not surfaced
- not measured
Explore specific needs, places and constraints across models. Investigate alternatives in the collected answers and trace which model and search mode surfaced them.
Illustrative patterns, not live findings. Each square is one prompt on one model in one mode.
Are your AI tools giving you the same shortlist?
One prompt. Three models. Each using its built-in web search.
“Which payroll providers should a growing team consider?”
| Supplier | Model A | Model B | Model C |
|---|---|---|---|
| Supplier A | Listed | Listed | Listed |
| Supplier B | Listed | Listed | Listed |
| Supplier C | Not listed | Listed | Not listed |
| Supplier D | Not listed | Not listed | Listed |
In this example, the first two suppliers recur in every answer. Models B and C each add an alternative to investigate. One prompt is a starting point; test a broader set before drawing conclusions.
Test a decision across models and search methods. Have your agent examine repeated recommendations, shared sources and alternatives worth investigating before you commit.
Investigate algorithmic monoculture: AI tools repeating the same options and assumptions. Agreement alone does not establish independent confirmation.
External web search uses a search provider you choose. Built-in web search uses the model provider’s own search.
Run across models within a budget
Choose models, web search settings and a spending limit through your agent. Our system runs the experiment. Check progress, inspect costs or stop the run through MCP.
Return to the evidence
Retrieve and search saved answers, inspect transcripts, and see what each run cost. Your agent can return to the original responses for further analysis without asking the models again. Failed or unrun prompts stay clearly marked.