About ManyMinds
The problem
Every LLM carries implicit biases shaped by its training data, geography, and corporate context. Gemini leans toward US/Western perspectives, DeepSeek toward Chinese ones, Mistral toward European framing. Users currently have no easy way to see these differences side-by-side or get a balanced reading.
What we do
ManyMinds takes one prompt, sends it to multiple LLMs in parallel, and produces a side-by-side comparison plus a neutral synthesis. We don’t claim the synthesis is objective truth. We claim that comparing perspectives makes bias visible.
Methodology
Bias detection runs across 10 versioned parameters — factual accuracy, completeness, cultural framing, political leaning, tone, source authority, omission, logical structure, terminology, and recency. Every score has a parameter page explaining how it’s computed.
The neutrality paradox
Our synthesis is itself an AI-generated perspective. The meta-LLM that produces it has its own training data, its own biases, and its own blind spots. We surface the raw responses from every LLM alongside the synthesis so you can see what we summarised — and disagree with us.
Bias in detecting bias
The bias taxonomy reflects the values and assumptions of its authors. Western-centric definitions of “bias” can themselves be biased. We version the taxonomy publicly and welcome cultural reviewers to challenge it.
Independence
ManyMinds takes no funding, partnerships, or preferential pricing from any LLM provider. We will never show ads. Any commercial relationships will be disclosed transparently.
Where we are today
ManyMinds is in public beta. It’s free for everyone while we listen. We’d love to hear what models you want, what use cases you have, and what would make this indispensable.
Contact
Email hello@manyminds.in. More feedback prompts on the Contact page.