Meshiva AI
Your guide to the archive · online
How to use Ask AI
- 01
Ask in plain language
A topic, a component, a beat, or a question — “tactile sensors for humanoid hands”, “how fleets avoid deadlocks”, or a single keyword like “thermal” all work.
- 02
Read the shortlist
Meshiva AI scans every story, scores it against your words, and returns the closest matches ranked by relevance — each with a match score and the reason it surfaced.
- 03
Go deeper
Tap any card to open the full report. Then keep the conversation going — refine your question, try another beat, or ask for something narrower.
- 04
Save what matters
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Questions about Ask AI
Everything you might want to know about the recommender. For general questions about Meshiva, see the full FAQ.
How does the recommendation work?
Meshiva AI reads the words you type and compares them against the title, description, and beat of every story in the archive. Each story is scored by how well it matches, then sorted by relevance and popularity. It is a real search over our live archive — not a random list.
Is this a language model like ChatGPT?
No. It is a fast, self-contained recommender that runs entirely in your browser. It does not call an external AI service and it never sends your queries anywhere. The “thinking” you see is our scoring pass over the archive.
Can I ask full questions?
Yes. Ask naturally — “how do fleets avoid deadlocks?” works as well as a single keyword. It pulls the meaningful terms out of your sentence and matches them against the archive.
Why did I get no results?
Our archive is written in English, so very narrow or off-topic queries may not match. If nothing is close, Meshiva AI falls back to the most-read stories. Try a broad term (a beat such as “fleet management”) or a component (“tactile sensors”).
How accurate is it?
It excels at finding stories by topic, component, or beat. It does not reason about opinions or produce new conclusions — it retrieves and ranks what Meshiva has published. Treat the match score as a relevance hint, not a verdict.
Are my queries stored?
No. Everything runs locally in your browser. Your keywords are not logged, saved, or used to train any model — consistent with our Privacy Policy.