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[ARTICLE · art-68147] src=iask.ai ↗ pub= topic=artificial-intelligence verified=true sentiment=↑ positive

iAsk.ai

IAsk.ai, an AI search engine for students and researchers, has surpassed 750 million searches, according to a Morningstar report citing Accesswire. The platform claims 67% better performance than other models and emphasizes accuracy, verifiable sources, and data privacy.

read1 min views1 publishedJul 22, 2026
iAsk.ai
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New We hit 750 million searchesAcademic, accurate

and

authoritative.

The AI search engine built for

students and researchers

Trusted by students and

researchers from top schools

What is iAsk? #

iAsk AI is an advanced free AI search

engine that enables users to ask

AI

questions and receive instant, accurate and

factual answers without

ever storing their data.

#

The AI learning engine

trusted by students

Millions of students worldwide use iAsk AI to

research, learn, and

explore new topics with

answers backed by verifiable sources.

#

The AI learning engine

trusted by students

Millions of students worldwide use iAsk AI to research, learn, and explore new topics with answers backed by verifiable sources.

#

Made specially

for research iAsk performed 67% better when compared to

other models, making it

the best search engine

for students and researchers

#

Trusted by millions of

students worldwide

Hear how students and researchers are using

iAsk for

their toughest assignments

I used to spend hours buried in PDFs trying to find the right citation. iAsk cut my literature review time in half.

Priya Nair

PhD @Stanford university

Most AI tools hallucinate sources. iAsk actually shows me where the answer came from, which matters a lot in writing thesis.

Jess Mah

Undergraduate @UC Berkeley

The video tutor genuinely feels like office hours. I used it the night before finals and it walked me through three problem sets.

Ayush Jaiswal

Graduate @UC Berkeley

Switched from ChatGPT for anything research-related. The accuracy difference is noticeable, especially with technical papers.

Daniel Kim

Research assistance @Harvard

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