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Private deployment
Enterprise AI knowledge base inside your infrastructure
On-premise deploymentNo data sent to public AI providersEnterprise integrations
Enterprise AI Knowledge Base
Private AI knowledge base for enterprise teams
Deploy a private AI assistant inside your infrastructure. Search Slack, Confluence, GitHub, Google Drive, Notion, internal documents, and databases with a secure enterprise RAG system.
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Public AI exposure
No company data sent to public AI providers
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Core source types
Chats, docs, code, drives, folders, and databases
Problem
Enterprise knowledge is fragmented, sensitive, and hard to search
Most companies already have the data they need. The issue is that it lives across chats, wikis, file shares, source code, and business systems. Public AI tools are not acceptable when data must stay private.
Security boundary
Many teams cannot send internal documents or conversations to external AI services.
Operational drag
Employees waste time searching multiple systems or asking the same questions repeatedly.
Scattered company knowledge
Important context lives across Slack, Confluence, GitHub, Drive, Notion, and internal folders.
Slow internal discovery
Traditional search misses context, wording, and knowledge buried in long documents or threads.
Compliance risk
Public AI workflows can conflict with security policy, regulatory controls, or customer commitments.
Knowledge loss
Critical process knowledge disappears when it depends on specific people instead of shared systems.
Solution
A private AI assistant built on your internal knowledge
InfyNapse creates an internal AI knowledge system for enterprise teams. It connects your data sources, indexes content with embeddings, and delivers grounded answers through retrieval-augmented generation.
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Enterprise AI search
Search company documents, conversations, repositories, and internal systems from one interface.
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Vector search and embeddings
Find relevant information by meaning, not only by exact keywords or document titles.
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Grounded RAG answers
Generate answers from retrieved internal sources instead of relying on unsupported model guesses.
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Private deployment control
Run the AI knowledge base inside your infrastructure with full control over access and data flow.
How It Works
From raw company data to grounded internal answers
Step 01
Connect company systems
InfyNapse connects to Slack, Confluence, GitHub, Google Drive, Notion, internal folders, and databases so the AI knowledge base can work on real company context.
Core components
SlackConfluenceGitHubGoogle DriveNotionDatabases
Security
Built for private infrastructure, regulated environments, and enterprise control
InfyNapse is designed for companies that need a private AI system, strict data boundaries, and operational control over how an enterprise AI knowledge base is deployed.
Deploy on premises or inside your private cloud environment.
Keep search, retrieval, and answer generation inside your security perimeter.
Control connectors, access rules, and data retention around each knowledge source.
Support enterprise security, compliance, and audit requirements without relying on public AI tools.
Integrations
Connect the systems where company knowledge already lives
Build one AI knowledge base across documents, conversations, source code, and structured data so teams can search company knowledge from a single place.
Slack and Microsoft Teams
Index discussions, decisions, incident context, and operational handoffs from internal chat channels.
Confluence and Notion
Search technical documentation, policies, product notes, and team knowledge bases.
GitHub and GitLab
Bring repositories, pull requests, issues, and engineering discussions into enterprise AI search.
Google Drive and shared folders
Ingest internal documents, spreadsheets, PDFs, presentations, and archived file structures.
Databases and business systems
Connect structured company data from SQL systems, exports, and internal operational platforms.
Custom internal services
Extend the private AI assistant with custom connectors for company-specific systems and APIs.
Use Cases
One internal AI knowledge system for every critical team
Engineering, support, compliance, and operations teams use the same private AI assistant while keeping enterprise data inside approved infrastructure.
Team use case
Engineering teams
Use enterprise AI search across repositories, architecture documents, runbooks, and technical discussions.
Knowledge sources
- GitHub repositories and pull requests
- Architecture decision records
- Engineering documentation and runbooks
Business value
- Reduce time spent searching across tools
- Speed up onboarding for new engineers
- Preserve technical context across teams
Example questions
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Where is the architecture document for the billing service?
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How does our deployment pipeline work?
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What changed in the authentication flow last quarter?
Request a private AI knowledge base demo
Tell us which systems you want to connect and which teams need access. We will use this to prepare a secure enterprise demo or pilot discussion.