AI CHATBOT

It Can Only Tell Visitors What You Actually Published

Zunoy's AI chatbot retrieves from your published content before answering, cites the entries it used, and scores its own confidence.

Answers From Your Content, Not a Guess

Zunoy's chatbot searches your published content for relevant passages before it answers, rather than answering from general training data. It generates its response from what it finds, and attaches the sources it used.

Generic chatbot

Answers from training data plus a short brief

Invents plausible detail when it doesn't know

A brief someone has to remember to update

No way to check where an answer came from

Zunoy's chatbot

Answers from passages retrieved out of your content

Weak retrieval scores expose the gap instead

Publishing content is what updates it

Every answer carries its sources

What Makes the Answers Trustworthy

Three properties do the work: retrieval happens before generation, sources travel with the answer, and every retrieval carries a relevance score that makes low-confidence responses identifiable rather than hidden.

Sources

Cited sources

Each answer carries the content entries it was built from.

Scoring

Relevance scoring

Every source has a score, so weak-match answers are visible.

Retrieval

Semantic retrieval

Matches meaning, so visitors needn't use your exact terminology.

Shared Index

One shared index

The same embeddings power admin search and the public chatbot.

Your Form Submissions Cannot Be Surfaced

Zunoy deliberately excludes form submission data from the embedding index. Submissions contain personal information belonging to identifiable people, and indexing it would turn a search feature into a compliance liability. The chatbot can discuss your published content; it structurally cannot leak what someone typed into your contact form.

Chatbot Questions Show You What's Missing

Every query logged

With its retrieval quality

Low-score questions ranked

As a content gap list

Real intent data

From your own visitors, not a keyword tool

FOR DEVELOPERS

Give Your Own AI Agents Access to This Content

The same retrieval layer is available as an API returning pre-chunked context, so agents you build can use your content as a knowledge source. Paired with the MCP server, your CMS becomes a content backend for AI experiences outside Zunoy. A support agent, an internal assistant, a product feature — all can draw from the same content your marketing site uses, without a second pipeline keeping a duplicate corpus in sync.

Pre-chunked RAG context over HTTP

The same index that powers on-site chat and admin search

No duplicate knowledge base to maintain

How It Works

Publishing is the only ongoing action required — indexing, retrieval, and citation happen without a maintenance workflow.

Enable Intelligence

Turn it on for the workspace and choose an embedding model.

Publish content as normal

Published entries are chunked and embedded automatically.

A visitor asks

In natural language, in their own words, on your live site.

Retrieve, answer, cite

Relevant passages are found, an answer is generated, sources attached.

Enable Intelligence

Turn it on for the workspace and choose an embedding model.

Publish content as normal

Published entries are chunked and embedded automatically.

A visitor asks

In natural language, in their own words, on your live site.

Retrieve, answer, cite

Relevant passages are found, an answer is generated, sources attached.

Enable Intelligence

Turn it on for the workspace and choose an embedding model.

Publish content as normal

Published entries are chunked and embedded automatically.

A visitor asks

In natural language, in their own words, on your live site.

Retrieve, answer, cite

Relevant passages are found, an answer is generated, sources attached.

Enable Intelligence

Turn it on for the workspace and choose an embedding model.

Publish content as normal

Published entries are chunked and embedded automatically.

A visitor asks

In natural language, in their own words, on your live site.

Retrieve, answer, cite

Relevant passages are found, an answer is generated, sources attached.

Enable Intelligence

Turn it on for the workspace and choose an embedding model.

Publish content as normal

Published entries are chunked and embedded automatically.

A visitor asks

In natural language, in their own words, on your live site.

Retrieve, answer, cite

Relevant passages are found, an answer is generated, sources attached.

Who This Is For

Support teams

Deflect repetitive questions using documentation you already maintain, without writing and syncing a separate help-bot knowledge base.

Answers update when your docs are published

Citations let visitors verify and read further

Content strategists

Unanswered questions ranked by frequency, which beats keyword research for accuracy about what your audience actually wants to know.

Content gaps identified by real visitor demand

Developers

A retrieval API for building your own agents rather than a hosted widget you can't extend or embed where you need it.

Pre-chunked context endpoint plus MCP tooling

Compliance-conscious teams

A grounded architecture that reduces fabrication risk, and an index that excludes personal data by design rather than by policy.

Submission data structurally out of scope

Common Questions

Does the chatbot answer from my own content?

Yes. It retrieves relevant passages from your published content and generates answers from them, rather than responding from general training data or a separately maintained knowledge base you have to keep updated.

How do I know when the chatbot is unsure?

Every answer records how many sources matched and the relevance score of the strongest match. Low scores indicate the question falls outside your published content, surfacing as a signal rather than being hidden.

Can the chatbot expose my form submissions?

No. Form submissions are deliberately excluded from the embedding index because they contain personal data, so the chatbot cannot surface information submitted through your forms under any query.

Can it show where an answer came from?

Yes. Each answer carries the sources it was generated from along with a relevance score per source, so responses can be verified and visitors can click through to read the full content.

Does it only match exact keywords?

No. Retrieval is semantic, matching on meaning, so visitors get relevant answers even when their phrasing differs entirely from the terminology used in your published content.

Is the chatbot separate from AI Studio?

No. It shares the same embedding index and retrieval layer powering AI Studio's semantic search and editing actions, so there is no second system to configure or keep synchronized with your content.

Stop Maintaining a Second Version of the Truth

Your documentation is already written. It may as well be able to answer questions.

Ask a question about Zunoy's products, pricing, or docs.

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