Platform · Workspaces
Workspaces: from your documents to answers you can trust, everywhere.
A ZenithAI workspace is a team’s shelf of documents that answers back: policies, manuals, circulars, contracts, price lists, past reports. You fill it once, keep it current, decide who may use it, and then ask it in plain language, in chat or from your own software. Every answer comes from those documents, names its sources, and says plainly when the documents don’t cover the question. It all runs on your organisation’s own servers.
The whole picture
Three ways in. Two ways to ask.
Documents reach a workspace from people, from public websites and from your own systems. Once ready, they answer people in chat and applications through the API, under the same access rules.
The journey
Seven stages, one governed workspace.
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01
Create a workspace
Anyone can create personal workspaces (up to 20 each) for their own work. Give it a name, such as HR policies 2026, and instructions for how it should answer, for example for branch staff, in simple words. Tell it standing facts to remember, a threshold, a convention, a GST rate, and every future chat starts knowing them.
For a department or the whole organisation, people with the Org workspace manager role create organisation workspaces and decide who may use each one.
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02
Fill it, three ways
- Upload in the app. PDF, Word (DOCX), Excel (XLSX), CSV, text and Markdown files, up to 3 MB each and 100 MB per workspace. Organisation workspaces are filled from Organisation Knowledge.
- Import from a website. One public page, or up to 25 pages from a site, fetched and indexed on your own hardware. Website Knowledge →
- Add from your own software. A document system, an HR portal or a nightly job can add a TXT, PDF, DOCX, XLSX or CSV file to its owner’s personal workspace through the API, when an administrator allows it for that key. Enterprise Knowledge API →
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03
Let it get ready
Each document is read and indexed in the background, and used for answers as soon as it is ready. Scanned PDFs are read with OCR on your server. Spreadsheets are kept as tables, so questions such as totals and averages are calculated, not guessed. A file that can’t be read is rejected straight away, and a document whose indexing fails says so and can simply be added again.
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05
Ask in chat
Start a chat, pick the workspace, and ask the whole workspace or one document in it. Under each answer ZenithAI shows what it looked at, such as From 3 of 3 documents or Searched 4 of 12 documents, with the names.
“How many casual leaves does a new joiner get in the first year?”
In a workspace chat, facts come only from the workspace documents. When they don’t hold the answer, ZenithAI says so and names the documents it checked, rather than filling the gap from general knowledge. The web is used only when the person asks for it, and every such search is logged.
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06
Ask from your applications
The same workspace answers your intranet, help desk, branch app or team chat bot through the Enterprise Knowledge API. Each answer carries its sources and a
foundflag that isfalsewhen the documents don’t say. An API key acts as the person who made it, so an application sees exactly the workspaces that person can open, and loses them the moment the person does. Asking stores nothing. -
07
Keep it current, and keep it governed
Answers are only as current as the documents, so retire a superseded circular when its replacement arrives: delete it in the app and add the new one. The list of questions the workspace couldn’t answer is your list of documents to add next. Administrators see API and chat usage, organisation workspaces keep an activity log, and server logs record ids and counts, not questions, answers or document names.
Where teams use them
One workspace per body of knowledge.
Illustrative patterns. Each workspace holds the documents its team already maintains, and answers the questions that team is asked every day.
| Workspace | Filled from | Who asks | A typical question |
|---|---|---|---|
| HR policies | Leave, travel and conduct policies | Every employee, in chat and the intranet | “What is the hotel limit for a manager in a metro city?” |
| Branch operations | Circulars and process notes, added by the document system every evening | Branch staff | “Which documents does a partnership firm need to open a current account?” |
| Product support | Manuals, warranty terms and the product site, imported | The help desk, before replying | “What is the warranty on the 1.5 tonne model?” |
| Academic regulations | Regulations, notices and the fee schedule | Students and faculty, through the portal | “What is the minimum attendance to sit the semester exam?” |
| Contracts | Signed agreements, added as they are signed | Legal and procurement, one contract at a time | “Does this agreement allow termination without notice?” |
| Monthly reporting | The month’s sales CSV | Managers | “What were total sales in the West region?” (calculated from the file) |
Why people trust the answers
Grounded, sourced, and honest about gaps.
A workspace answer is built to be checked. It comes from your documents, names them, calculates numbers from the data, and says “not in the documents” instead of guessing.
- 01Only your documents · facts in a workspace chat come from the workspace, not from general knowledge or an uninvited web search
- 02Sources with every answer · the documents behind it, so anyone can open the policy and check
- 03“Not found” is an answer · in chat it is said plainly; through the API it is a
foundflag your software can read - 04Access follows the person · in chat and through the API alike, nobody sees a workspace they couldn’t open in the app
- 05On your own servers · documents, indexing and answers stay inside your infrastructure. Security & governance →
Wrong answers are reduced, not ruled out. Show the sources and let people check anything that matters. ZenithAI’s architecture supports data-residency and data-minimisation objectives, including obligations under India’s DPDP Act; it is not a certification.
Step-by-step guides
Every stage, in the documentation.
| Stage | For people at work | For developers and administrators |
|---|---|---|
| Create and fill | Workspaces: create, add documents, ask | API: add a document and check its status |
| Share | Share with your team | Organisations and Org workspace managers |
| Ask | Chat with ZenithAI | Ask your workspace from your app |
| Govern | Web search in workspace chats | Let a key add documents |
Questions
Workspaces, answered.
What is a ZenithAI workspace?
How do documents get into a workspace?
Who can see a workspace?
Does a workspace answer from outside its documents?
Can our own applications use a workspace?
Where are workspace documents stored?
How do we keep a workspace up to date?
Why this matters: Where do your documents go when you ask AI?, One company, one answer: a private internal knowledge base and AI for enterprise knowledge management: what the research says.
Bring a few real documents
Build a workspace with us. Ask it your hardest question.
In a demonstration, put your own policies or manuals in a workspace, share it, and ask it in chat and through the API, including a question the documents can’t answer.