Knowledge Files for Controlled AI Sources
Documents, metadata, permissions and index status in one place — before AI answers.
Build Knowledge Files as the controlled source layer
Knowledge Files are the clean foundation of document & knowledge AI. The module connects SharePoint, DMS, email, file shares or business systems, extracts metadata and checks permissions before indexing. You can see which sources may be used, which documents still need review and which content is excluded because of retention rules, permissions or poor quality.
Knowledge Files define what AI is allowed to know
Document AI becomes reliable only when its sources are controlled. Knowledge Files separate approved sources from raw repositories, duplicates, outdated versions and documents with unclear permissions.
Typical use cases include contract archives, purchasing documents, policies, support emails, invoices, quality evidence and project files. Every source receives metadata, an owner, retention rules and an index status before it is used in knowledge chat or contract review.
Permissions, versions and quality remain part of the workflow
Each sync checks whether a document is new, changed, blocked or deleted. Permissions from Microsoft 365, a DMS, file shares or business systems are preserved and checked before retrieval.
Unclear files do not silently enter the index. They land in a review queue where a person can approve, defer, clean up or exclude the document.
Knowledge Files feed chat, review and the knowledge graph
The knowledge chat uses Knowledge Files for cited answers, contract review uses them for rule checks, and Deep Knowledge extracts entities and relationships from them. The source layer is not just storage; it is the foundation for every AI workflow.
AI, data and approvals in Knowledge Files for Controlled AI Sources
AI in this module is source-grounded. It does not search files indiscriminately; it uses approved documents, role permissions, metadata and business rules. Connect sources, Extract metadata, Preserve permissions, Audit and retention become a controlled process: AI finds evidence, marks uncertainty, shows source passages and stops when human review is required.
Risky cases need explicit stop points: low model confidence, missing sources, permission conflicts, cost impact or customer-facing communication enter a review queue. That keeps speed high without giving up control, traceability or privacy.
Which data and integrations the module needs
For Knowledge Files for Controlled AI Sources to work in daily operations, the data currently scattered across spreadsheets, email, business systems and file stores has to be modelled properly. The core inputs are roles, status values, deadlines, documents, comments, owners and the rules behind Connect sources and Extract metadata.
A custom build connects that data to existing systems instead of forcing teams to maintain it twice: ERP, accounting, DMS, Microsoft 365, email, ticketing systems or mobile apps can be connected depending on the process. The goal is not the longest integration list; it is a clear source of truth.
Why a custom build can beat standard software here
Standard software starts faster and can be the right choice for simple workflows. A custom solution becomes stronger when Knowledge Files for Controlled AI Sources has to fit exact roles, data ownership, approval paths, hosting requirements and internal exceptions. Then process fit matters as much as feature count.
The honest downside: a custom build needs more discovery, rollout work and prioritisation at the beginning. The upside comes afterwards: fewer workarounds, no per-seat logic, controllable hosting, owned source code and modules that can grow as requirements change.
What this solution covers
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Connect sources
DMS, SharePoint, email, file shares, CRM, ERP or business applications are connected as controlled sources.
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Extract metadata
Document type, customer, counterparty, deadline, version, cost center and validity are captured structurally.
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Preserve permissions
Role permissions are checked before search and answer; AI does not get a bypass around access rights.
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Audit and retention
Index changes, approvals, blocks and retention rules stay traceable.
Frequently asked questions
Can existing document permissions be reused?
Yes. Permissions from existing systems can be preserved during indexing and checked before every search.
What happens to outdated or blocked documents?
They are excluded from answers or placed in a review queue, depending on the approval process you want.
Do all documents need to be indexed immediately?
No. A useful start is a clearly scoped source set, such as contracts, policies or support emails. The collection can then be expanded iteratively.