Turn scattered knowledge into
trusted intelligence
Most new tools start empty. Ingestion seeds structured, verified Q&A on day one – so your team has answers before anyone has to ask.
Available on the Enterprise Plan.
Inc. 100 Knowledge Objects per month
An appetite to learn
Knowledge starts its life in all kinds of places. Ingestion
lets you capture and structure those everyday nuggets that
might otherwise never get shared.
High-signal Q&A, not noise
Turn your document graveyard into structured, verified knowledge in minutes. Power high-volume migrations via our API or web interface.
Ready to review, instantly
Our AI pipeline automatically converts content into structured, tagged, and confidence scored Q&A. Your experts validate high-quality content instead of authoring from scratch.
Activate Confluence data
Connect your Confluence Cloud spaces to transform static pages into verified Q&A pairs that are easier to find, trust, and maintain.
Deploy your intelligence
Put your data to work. Our MCP server lets AI agents retrieve and update SME-approved answers.
Always served fresh
We’ve been building tools to keep knowledge
up-to-date for over 17 years, once in Stack Internal
these battle-hardened tools can be put to work.
Q&A
Our time-tested Q&A surfaces trusted answers to the top, making it easy for both humans and AI to parse.
Enhanced Search
Let the AI summarize multiple answers across your knowledge base into new insights.
Maintainable long term
Unlike static Wikis that go stale, your community is alerted when content needs to be reviewed and updated so it stays relevant and accurate.
Knowledge is everywhere, except where you need it
Eliminate the cold start
Skip the manual setup. Ingestion converts raw files into a verified Q&A repository immediately, so you can start driving adoption on day one.
Stop the endless search cycle
Your best technical answers shouldn’t be buried in a chat threads or notes. Turn those fleeting moments of brilliance into permanent, searchable knowledge.
Reduce hallucinations at source
Your AI agents are only as good as your institutional data. Ensure they act on structured, expert-verified facts, not outdated noise.
Frequently Asked Questions
Ingestion is Stack Internal’s way of importing content.
Stack Internal’s Ingestion feature pre-populates the platform with verified technical knowledge before users are onboarded. By converting existing scattered PDFs and Markdown files into structured Q&A, it ensures the first users to search the platform find immediate, relevant answers – driving usage and adoption from Day 1.
Ingestion is a subscription-based add-on. All Stack Internal Enterprise sites receive a base allotment of 100 Knowledge Objects per month (measured by human approved Q&A pairs) so users can experience the power of the Ingestion tool.
For higher volume needs, organizations can purchase premium tiered add-ons. For more information, see the Ingestion Subscription and Billing article.
Customers can import content through three primary channels: manual file uploads within the web interface, programmatic ingestion via a REST API endpoint, or the Confluence Cloud connector, which establishes a direct link between Confluence spaces and Stack Internal to automatically ingest and convert pages into structured Q&A.
Customers can ingest Confluence pages, PDFs, plain text like Markdown & HTML files, images (.jpeg, .jpg, .png, .bmp, .heif, .tiff) and Microsoft 365 files (.docx, .xlsx, .pptx).
Upon importing, a duplication check runs to determine if an identical or similar document already exists in the Stack Internal instance. If a duplicate is detected, it’s skipped to ensure only net-new knowledge is sent to the review queue where human experts validate the content.
The Confluence Cloud connector also ensures only new or updated pages are ingested to prevent overlap.
Ingestion’s AI pipeline intelligently chunks, cleans, and converts raw text into structured, atomic Q&A pairs. These posts are automatically tagged, mapped to users, and scored for confidence before being routed to experts for final review.
By converting fragmented, unstructured content into verified units of knowledge, institutional data is optimized for both human discovery and AI retrieval.
No. Customer data is not used to train large language models (LLMs), and external LLM providers do not have access to your data. All ingestion and AI-enhancement occurs within a secure, logically isolated environment In Azure to keep your data completely private.
