An index thatreads, not justmatches keywords.
“AI web indexer” gets used loosely — usually to mean a keyword search with a language model summarising the results. The real version changes what gets kept in the first place: meaning instead of keywords, filed by document type, ready to answer instantly.
ai web indexer/
├── reads for/
│ ├── keywords classic index
│ └── meaning ai index
├── files by/
│ ├── "web page" classic index
│ └── document type ai index
└── answers in/
├── a search + a fetch classic
└── milliseconds ai indexThree things, and none of them is the sentence at the end.
Reads for meaning
A keyword index matches the words in your question against the words on a page. An AI web indexer reads the page, keeps what it means, and can match a question phrased nothing like the source — because the comparison happens on meaning, not spelling.
Files by what it is
A patent, a court judgment, a clinical trial and a news article are not the same kind of document, and treating them all as generic "web pages" throws away exactly the structure that makes each one trustworthy. Filing by type keeps identifiers, jurisdiction and status attached to what's read.
Answers in milliseconds
Reading is done ahead of time, so answering isn't a live fetch-and-summarise — it's a lookup against a store that's already been read, understood and organised. These are the live figures from the running system.
Answers in milliseconds — live
query → vector on the GPU pool · payload-indexed SafeSearch filter · deterministic result cache
A chat layer on an old index is not an AI web indexer.
Bolting a language model onto a keyword search doesn't make the index AI — it makes a keyword index with better phrasing on top of results it still can't judge for relevance.
An AI web indexer changes what gets stored, not just what gets said back. The intelligence has to be in the reading and the filing, or there's nothing underneath the fluent-sounding answer.
That's the difference between summarising a page one has been handed and reasoning over a library one has actually read.
What does "AI-powered" actually mean for a web indexer?
It means the reading step uses a model to understand a page's meaning rather than just extracting its words — so what's stored is content organised by what it means and what kind of document it is, not a list of keyword-to-page pointers.
Isn't every search engine "AI" now?
Most add an AI-written summary on top of the same link-based results they always returned. That's an AI layer on an old index, not an AI index. What changes the ceiling on the answer is what's stored underneath, not what writes the sentence at the end.
How does askFinz decide what kind of document something is?
Reading is staged — cheap methods handle the overwhelming majority of pages, and progressively more capable ones step in only for pages that need it. See how the index works for the three stages, without the specifics that would let a page defeat them.
Can I use this indexer directly, as an API?
Not as a standalone feed today — it powers askFinz's own apps. See an AI index for every customer for what that means in practice.
See the difference in one search.
The clearest way to tell an AI index from a keyword index with a chat window on top is to ask it something specific and see what comes back — a passage that answers the question, or a page you still have to go read.