Enterprise AI search and chat grounded in your company knowledge
Ask natural language questions across the tools your company already uses. LINKENCE searches indexed Gmail, Outlook, Drive, SharePoint, Slack, Teams, Jira, Confluence, GitHub, Bitbucket, Box, calendars, and uploaded files with citations and access controls.
What did Legal decide about the new enterprise refund policy?
The latest policy (effective this quarter) extends refund eligibility to 90 days for enterprise-tier accounts and requires a signed amendment for any exception.
Sources
Unified enterprise knowledge search
Teams search for enterprise AI search, AI knowledge base, company knowledge assistant, internal search engine, enterprise AI copilot, and AI chat with citations when tribal knowledge is scattered across SaaS apps. AI Chat gives employees one place to query internal knowledge instead of opening inboxes, drives, Slack threads, Jira issues, Confluence spaces, and repository tabs one by one.
Retrieval blends semantic search, keyword search, source filters, and reranking so exact terms like a Jira key still matter while natural questions find the right paragraph. That is permission-aware RAG: scoped sources, hybrid retrieval, and grounded answers.
What AI Chat can search
Depending on the connectors your workspace admin enables, Linkence AI Chat can retrieve and cite answers from the sources below—always scoped by permissions and indexing rules.
- Uploaded PDFs, DOCX files, spreadsheets, presentations, and text files
- Gmail and Outlook threads
- Google Drive, OneDrive, SharePoint, and Box documents
- Slack and Microsoft Teams channel context
- Jira issues, comments, status, and project context
- Confluence pages, specs, runbooks, and internal documentation
- GitHub and Bitbucket repository documentation, issues, pull requests, and review context
- Google Calendar and Outlook Calendar meeting context
What makes Linkence different from a normal chatbot?
Normal chatbots answer from one uploaded document or a narrow knowledge base. Linkence searches across your connected business systems — Gmail, Outlook, Drive, SharePoint, Slack, Teams, Jira, Confluence, GitHub, Bitbucket, Box, calendars, and uploaded files — then returns grounded answers with citations and access controls.
Not just a chatbot over documents
Buyers want semantic search for company documents and search across SaaS apps without maintaining a separate enterprise search appliance. Linkence connects live systems so answers reflect mail, tickets, chat, wikis, and repos together—not only static uploads.
Example questions users can ask
- “What is our latest customer refund policy?”
- “Which source explains the enterprise onboarding process?”
- “Summarize the full history of this customer escalation.”
- “What did engineering decide about this bug?”
- “Which Jira tickets, Slack threads, and Confluence pages mention this incident?”
- “Where is the current access review process documented?”
- “What did we promise this customer in the last email thread?”
- “What did the team decide in Slack about the launch delay?”
Best-fit teams
This capability is most useful for:
- Customer support teams that need faster cited answers
- Sales teams that need account context and follow-up reminders
- Operations teams that coordinate work across email, chat, docs, and tickets
- Engineering teams that need Jira, Confluence, GitHub, Slack, and incident context
- HR and admin teams that answer repeated policy and onboarding questions
Common AI Chat use cases
- Internal knowledge base chatbot
- Policy and SOP search
- Customer support answer generation
- Engineering incident and release search
- Sales account history search
- Meeting and email context search
- HR and onboarding assistant
- Compliance evidence search
Permission-aware RAG with citations
Every answer is grounded in indexed sources and can show citations so users can verify the document, mail thread, page, issue, or channel message behind the response. Permission-aware retrieval keeps restricted documents and connector content out of answers for users who should not see them.
Quick, General, and Deep response modes let teams choose speed or depth. Deep mode is useful for complex policy, support, engineering, and operations questions where multiple sources need to be compared before an answer is safe.
Search scope for teams and workflows
Users can scope chat to Documents, Gmail, Outlook, Calendar, Jira, GitHub, Confluence, Slack, Bitbucket, and other connected sources that are active in the workspace. Narrowing scope improves relevance when a user needs only HR policies, customer emails, engineering tickets, or meeting context.
AI Chat shares the same knowledge layer as Actions, Triggers, and Deadlines, so a support answer can become a drafted reply, an operations question can become a Jira task, and a commitment found in chat can become a tracked deadline.
Common workflows
Ask questions across company documents and SaaS apps
Search uploaded PDFs, DOCX files, spreadsheets, Google Drive folders, SharePoint libraries, Confluence pages, Slack messages, Jira issues, and email threads from one chat surface.
Find policy answers with source links
Answer questions like what is our refund policy, how do we onboard contractors, or which escalation path applies, then cite the source paragraph for review.
Summarize scattered project history
Combine emails, calendar events, Jira tickets, pull request notes, and wiki pages into a concise project or incident summary.
Frequently asked questions
- Does AI Chat send email or change tickets on its own?
- AI Chat is read first for knowledge. When you use Actions, sensitive writes pause for human approval before anything is sent or updated.
- Can AI Chat work as an internal search engine?
- Yes. LINKENCE is designed as an AI search layer over private company knowledge. Users can ask natural language questions, filter by source, and verify answers through citations.
- Can we limit answers to legal, HR, support, or engineering content only?
- Yes. Source filters and RBAC boundaries restrict which connectors, documents, labels, folders, spaces, or projects retrieval can use for each user or team.
- How does this relate to enterprise AI copilot expectations?
- AI Chat is the retrieval and synthesis layer: cited answers across connectors. Actions adds approval-gated automation when a workflow needs to write back to tools.