Built a multi-AI search tool. No login, No data collection. Looking for feedback
I made a meta-search engine that sends one query to multiple AI services in parallel and synthesizes their answers so you can see where they agree and where they diverge. No login required and no data collected. Looking for your honest feedback.
Problem I solved
I’ve been doing the same dumb workflow for months: same prompt, three tabs, then I sit there comparing answers like I’m fact-checking three opinion columns.
Each AI is good at different things. Perplexity cites well. Gemini is fresh. ChatGPT reasons through messy questions. Grok catches stuff on X before it hits the news. But they also fail in different ways. If you only use one, you’re basically betting on a single columnist who might be brilliant, biased, or confidently wrong.
Perplexity’s Model Council is a step in the right direction, but it’s still one product. What I wanted was cross-vendor: one query, multiple services, see where they agree and where they don’t.
My solution
Still early, but the idea is simple: for anything that actually matters. For research, purchases, health questions, one model isn’t enough. You want consensus and conflict visible, not smoothed into one confident paragraph.
I made a search layer above the chatbots. You ask once; it hits ChatGPT, Gemini, Perplexity, Grok, and others in parallel, then synthesizes the results instead of hiding disagreements.
The hard part isn’t “another chatbot.” It’s that these aren’t static web pages you can crawl. So the backend uses browser agents to interact with them in real time. More orchestration than classic search indexing.
Curious if anyone else is doing this multi-tab reconciliation manually, or if you’ve found something that already solves it.
