Knowledge Assistants
AI Internal Search for Confluence
Searches across your internal tools from one place with AI-ranked results, connected natively to Confluence so it indexes spaces, pages and attachments…
Knowledge Assistants
AI Internal Search
One search bar returns ranked results across every connected tool, instead of five separate searches.
Finding one file shouldn't mean checking Google Drive, SharePoint, Notion, Confluence and Slack in turn. AI Internal Search gives your team one search bar across the tools you already use, with ranked results and a short cited snippet from each, so people can judge which document to open. Permission groups keep each team's results to what they may see, and your content stays where it lives.
- One search bar across up to three connected tools
- Ranked results with a cited snippet to judge each document
- Different teams see only the results they are allowed
$8,900
20–30 working days
Optional maintenance $445/mo
What it is
AI Internal Search is a unified search layer over your existing tools, Google Drive, SharePoint, Notion, Confluence and Slack among them, that returns ranked results with a short cited snippet from each, so people find the right document themselves instead of searching five places one at a time.
Why businesses buy it
Every time someone searches three tools for one file, or gives up and asks a colleague, you lose a few minutes and someone else's focus. Across a team of fifty, that adds up to days every month. AI Internal Search ranks results from all your connected tools in one place, so people find the right document on the first try and keep working. It suits teams who want to choose from results rather than trust a single generated answer. The Scope Card fixes the tools, document volume, permission groups and benchmark tests before you order.
Problems this solves
People search five different tools one at a time to find one file
One search covers up to three of your existing sources, such as Google Drive, Notion or Slack. Results come back ranked, each with a short cited snippet.
Search results show a title but not whether it is the right file
Every result carries a snippet from the document with its citation. People can judge relevance before opening anything, which saves clicking through near-duplicates and old drafts that look almost identical.
Staff rebuild documents that already exist somewhere else
With up to 2,000 documents indexed together, existing work is far easier to spot. A monthly content refresh keeps the index current as new files are added.
Finance and HR files must stay with the right teams
Up to three permission groups shape what each person can see in results. Sensitive material appears only for the right people. Wider access to search does not mean wider access to files.
A good fit if
Your files are spread across several tools, such as Google Drive, SharePoint, Notion, Confluence and Slack, and finding one means checking each in turn.
You want a search bar people type a query into, not a chatbot they have a conversation with.
You have up to 2,000 indexed documents across up to 3 connected sources, and different teams should see different results.
You want ranked results with a short cited snippet, so people can judge which document to open rather than trust one answer.
Not the right fit if
You want one synthesized answer to a question, not a ranked list of results to open yourself. See AI Company Knowledge Hub.
Your search is really about one document set, such as a manual, not everything across your tools. See AI Document Q&A.
You want to know what people search for and cannot find, not a better way to find it. See AI Knowledge Gap Finder.
Nothing is organized enough to search yet. See AI Knowledge Base Builder, which structures scattered material before indexing it.
How it works
- We connect up to 3 of your existing tools, such as Google Drive, SharePoint, Notion or Confluence, and index up to 2,000 documents from them.
- Every document is embedded so it can be matched by meaning, not just by keyword, and tagged to the permission group it belongs to.
- Someone types a query into the search bar, on your web app, Slack or Microsoft Teams, the same way they would search any one tool.
- Internal Search ranks the matching documents across all connected sources at once, with a short cited snippet from each so the reader can judge relevance before opening it.
- Up to 3 permission groups keep results scoped to what each person is already allowed to see, in every connected source, not just the one they searched last.
- A monthly refresh keeps the index current as files change, and we test the search against 60 benchmark queries with an accuracy report before launch.
What you provide within 72 hours
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
- Access to the tools this search should cover, such as Google Drive, SharePoint, Notion or Confluence.
- Your user list and the permission groups results should respect.
- 30 sample search queries, with the results you expect to see for each.
- Workspace admin access for sign-in on your chosen interface.
- Admin access and API keys for every connected system, shared by adding our team as a user or creating a key you control, never by email.
- Your business information (company basics, hours and brand voice), shared during intake.
- One decision-maker who can approve the permission groups before launch.
- An API key for your own AI model account (for example OpenAI or Google Gemini), created for this build with a spending limit.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
Intake confirmed, with the connected tools, permission groups and sample queries agreed.
Weeks 1–2
Documents indexed and embedded from every connected tool.
Week 3
Ranking, snippet and permission-group logic built and connected to your chosen interface.
Weeks 3–4
Tested against 60 benchmark queries, with an accuracy report delivered.
Week 4
Your review and two rounds of changes.
Go-live
Live, with a recorded handoff session, and 30 days of support starts.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $8,900 |
| Express | 15–25 working days | $10,000 |
| Rush | 10–20 working days | $11,150 |
What you receive at handover
- Internal search running in one interface (web app, Slack or Teams) for up to 50 users
- Connections to up to three content sources, indexing up to 2,000 documents
- Ranking, prompt and guardrail configuration with up to three permission groups
- Test report with 60 benchmark questions and an accuracy report
- Admin guide and recorded handoff session
- 30 days of post-launch support
Expected benefits and how to measure them
- Can save the time people spend hunting for files across several tools.
- Helps teams reuse existing work instead of starting again.
- Time to find a known document
- Choose ten documents and time how long colleagues take to find each, before launch and after.
- 'Where is it' messages
- Count chat messages asking where a file or page lives over four weeks before launch and four weeks after.
- Result accuracy
- Compare the benchmark accuracy report from launch with a re-run after a few monthly refreshes.
Before you start: List which tools hold your documents and roughly how many files each contains. Time a handful of searches people run every week.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
Running costs
You pay for the build once. Running Internal Search costs roughly $50 to $300 a month in your own accounts, covering AI model usage, the vector database and hosting, and it moves with document volume and how many of your up to 50 users search each day.
AI usage during the build and testing is billed to your own accounts too, so every provider relationship stays in your name.
Ask about running costsCustom requirements
If you need more than 3 connected tools, more than 2,000 documents, or a second interface, add a note at checkout for a written Change Quote. Your order still runs on its normal timeline. Larger or bespoke projects go through the Custom AI request form.
Request a custom versionKeep it running
We recommend monthly maintenance: monitoring, fixes and monthly change hours, covering a new connected tool or updated permission groups. Maintenance starts after the 30 days of support and can be cancelled any month.
$445/mo (5% of the build price a month, includes 4 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance worksHow this compares
| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | An enterprise search tool charges per seat every month regardless of use | A custom search build is quoted after weeks of discovery | Ours is one fixed price, shown before you buy |
| Coverage | An enterprise search tool often supports only its own vendor's other apps | An agency build depends on what was scoped | Ours connects up to 3 tools you already use, in one build |
| Result format | Some search tools return a bare list of filenames with no context | An agency build depends on what was scoped | Ours returns ranked results with a cited snippet from each |
| Delivery | An enterprise search tool is instant to sign up but slow to tune | An agency build usually takes several weeks | Ours has a fixed delivery time shown before you buy, with faster options |
Questions about this product
How is AI Internal Search different from AI Company Knowledge Hub?
AI Company Knowledge Hub gives one synthesized, conversational answer to a question. Internal Search works like a search bar: you type a query and get a ranked list of results with a short cited snippet from each, across up to 3 connected tools. Choose Search when people want to find and open the right document themselves.
Which tools can AI Internal Search connect to?
Up to 3 of your existing tools, commonly Google Drive, SharePoint, Notion, Confluence or Slack, indexing up to 2,000 documents between them. You choose which 3 during intake based on where your team's files actually live. A fourth source can be added later as a maintenance change or a Change Quote.
Does AI Internal Search give one answer or a list of results?
A ranked list, one of the reasons it differs from a Q&A assistant. Each result shows a short cited snippet so the reader can judge relevance before opening the document, rather than reading one synthesized paragraph. People who want a single conversational answer instead should look at AI Company Knowledge Hub.
How much does AI Internal Search cost to run each month?
Roughly $50 to $300 a month in your own accounts, covering AI model usage, the vector database and hosting. It moves with how much you index and how often your up to 50 users search. The build itself is paid once and covers connecting your tools, ranking and permission logic.
Do AI Internal Search results respect who is allowed to see what?
Yes. Up to 3 permission groups are configured before launch, and every result is filtered against them before it is shown, across all connected tools at once. A document someone cannot open in its source system will not appear in their results, even if the words match closely.
How long does AI Internal Search take to launch?
Delivery runs on a fixed schedule from a complete intake, and the delivery panel shows that date plus express and rush options before you buy. Most of the time goes into connecting and indexing your tools, building ranking and permission logic, and testing against 60 benchmark queries before your review.
One search bar for every tool you already use.
Order AI Internal Search and it goes live on a fixed delivery date, ranking results across up to 3 of your connected tools from one search bar.
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