Structured multi-model reasoning

Make AI models work through the problem together.

RelayMRL turns Claude, ChatGPT, Perplexity, and Grok into one reasoning workflow. Compare answers, relay arguments, surface disagreement, and synthesize a stronger final take.

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Compare model judgment before a product, code, or strategy decision

Relay a strong answer to another model for pushback and missed risks

Turn scattered model outputs into a synthesis you can actually use

Use Perplexity for current evidence, then relay the result to another model for critique

Have one model review the implementation plan another model produced

How it works

Ask one problem

Start with a question, draft, code issue, research prompt, or decision you do not want to trust to one model.

Relay the reasoning

Send one model's answer to another for challenge, refinement, missing context, or a different angle.

Compare the differences

Use agreement and disagreement as signals. Where models converge, the answer may be stronger. Where they split, you have something worth inspecting.

Decide with context

Synthesize what each model contributed before choosing a final direction.

Common questions

Is this just a chatbot aggregator?

No. The point is not access to more chat boxes. RelayMRL gives structure to multi-model thinking: ask, relay, challenge, compare, and synthesize.

Does it eliminate hallucinations?

No AI workflow can promise that. RelayMRL helps you surface disagreement, compare reasoning, and make better-informed judgments instead of accepting one polished answer.

Who gets the most value from it?

AI builders, vibe coders, founders, researchers, product people, strategists, writers, students, and anyone already bouncing work between Claude, ChatGPT, Perplexity, Grok, or Gemini.

Why not just use the best model?

The best model depends on the task. For serious work, different models often catch different issues, assumptions, and tradeoffs.