Custom AI Chatbots
Internal Knowledge Search Chatbot
Internal knowledge search is the ability for employees to ask a question and get a direct answer pulled from company documentation, rather than digging through folders, wikis, and old Slack threads. A custom chatbot indexes existing internal content and answers questions conversationally inside the tools employees already use.
01The problem employees describe
New and tenured employees alike waste time hunting for answers that already exist somewhere in the company: the current PTO policy, the correct expense approval threshold, how to submit a specific IT request. The information exists, but it is scattered across Confluence, shared drives, and old email threads.
The default fallback is asking a coworker or manager, which interrupts their work too. Multiply that across a company of any size and the same question gets answered dozens of times a month by different people.
02What the current approach costs
Studies on workplace knowledge search consistently find employees spend 1 to 3 hours a week looking for internal information. At an average loaded cost of $30 to $45 an hour, that is $130 to $580 a month per employee, which scales quickly across a 50 or 100 person company.
The interruption cost to the person answering the question is separate and often larger, since context switching to answer a colleague's question typically costs 10 to 20 minutes of focused work time, not just the minute spent replying.
03How the chatbot works
- Step 01
Index content
The chatbot connects to Confluence, Google Workspace, Microsoft 365 SharePoint, and designated Slack channels to index existing documentation.
- Step 02
Understand the question
An employee asks a question in Slack or a browser widget in plain language, no keyword search required.
- Step 03
Retrieve and answer
The chatbot finds the most relevant source content and generates a direct answer with a link back to the original document.
- Step 04
Flag gaps
Unanswerable questions are logged so document owners know which policies need to be written or updated.
- Step 05
Respect permissions
Answers only draw from documents the requesting employee already has access to, respecting existing permission structures.
04Project specifics
| Spec | Detail |
|---|---|
| Maps to | Custom AI Chatbots |
| Typical timeline | 3 to 6 weeks |
| Typical price band | $6,000 to $18,000 for setup, plus monthly hosting |
| Systems commonly involved | Confluence, Google Workspace, Microsoft 365, Slack |
| Typical time saved per employee | 1 to 2 hours per week (typical range) |
05Common questions
Does it expose confidential documents to everyone?
No, answers are filtered by the same permissions employees already have in the source systems.
How current is the information?
The index refreshes on a schedule, typically daily, so recently updated documents are reflected quickly.
Audit your internal documentation with us
We assess how much of your existing content is search-ready before scoping the chatbot build.
FAQQuestions
Common questions
What sources can it search?
Commonly Confluence, Google Workspace, Microsoft 365 SharePoint, and designated Slack channels, plus any system with an accessible API.
Does it replace our wiki?
No, it sits on top of your existing wiki and documents rather than replacing them.
What is the honest limit here?
If the underlying documentation is outdated or missing, the chatbot will surface that gap rather than invent an answer, but it cannot fix bad source content on its own.
Can it answer questions about live data, like current headcount?
Only if connected to a live data source; otherwise it answers from static documentation and will say so when it cannot find current data.
Last reviewed 2026-08-16
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- Custom AI Chatbots
A custom AI chatbot answers from a company's own content and connects to that company's systems. Lingows AI builds chat for websites, phone lines, messaging channels, and internal knowledge bases, with retrieval grounded in approved sources and a defined handoff to a person.
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- AI Implementation for SaaS and Technology Companies
A SaaS AI agent reads support tickets, product analytics, or bug reports and completes a defined task such as drafting a ticket response or routing an engineering bug, built to operate inside a SOC 2 control environment so customer data handling matches commitments already made in your security questionnaire and trust page.
Scope ai chatbot for internal knowledge search for your volume
Bring the monthly volume, the systems involved, and who reviews the output today. Lingows AI will return a build scope, a timeline range, and a running cost.