AI Agent Automation Platforms
How do we build a StackAI Knowledge Base from SharePoint/PDFs and require citations in answers?
7 min read
Quick Answer: Use StackAI’s Enterprise AI Transformation Platform to ingest content from SharePoint and PDFs into a governed Knowledge Base, then connect that Knowledge Base to an agent configured with Retrieval-Augmented Generation (RAG) and “citations required” response policies so every answer includes source references.
Frequently Asked Questions
How do we create a StackAI Knowledge Base from SharePoint and PDF content?
Short Answer: Connect SharePoint as a source, upload or sync your PDFs, and let StackAI index them into a unified Knowledge Base that agents can query with Retrieval-Augmented Generation.
Expanded Explanation:
In StackAI, a Knowledge Base is a governed collection of documents and data that agents can search, retrieve, and cite. For SharePoint, you typically configure a connector or integration that can read from specific document libraries or sites, then set sync rules (what to pull, how often, and with which permissions). For PDFs and other unstructured files, you upload them directly or via a storage integration; StackAI uses built-in OCR and text extraction to turn them into structured, searchable chunks.
Once ingested, the content is normalized and indexed for semantic search. This means your policies, contracts, SOPs, and reference documents stored in SharePoint and PDF repositories become a consistent, queryable Knowledge Base. Agents then use one-click Retrieval-Augmented Generation to answer questions with grounded context from these sources, including links or identifiers back to the original documents.
Key Takeaways:
- StackAI centralizes SharePoint sites and PDFs into a single governed Knowledge Base.
- OCR and text extraction make scans, forms, and PDFs searchable and usable for RAG.
What are the steps to build and connect this Knowledge Base to an agent?
Short Answer: Define data sources, ingest and sync them into a Knowledge Base, then attach that Knowledge Base to an agent configured to use RAG with citations.
Expanded Explanation:
From an implementation standpoint, you’re setting up two layers: (1) the content layer (SharePoint + PDFs as a Knowledge Base) and (2) the agent layer (how end users query that content, which interfaces they use, and what governance applies). IT or Enterprise Architecture teams usually own the initial configuration, including access control and sync schedules, then expose the agent to business users through forms, web apps, or existing tools.
Agents built on StackAI can be deployed behind interfaces like claim processing forms, IT ticket triage, or internal policy search, all backed by the same Knowledge Base. Operationally, you want to define who can add documents, how updates are promoted (e.g., via publishing controls), and how you monitor performance (runs, errors, tokens, and retrieval quality).
Steps:
- Connect sources: Configure SharePoint integration and define which sites/libraries to sync; upload or connect the storage holding your PDFs.
- Build the Knowledge Base: Let StackAI index and chunk documents with OCR/text extraction, then verify coverage and metadata (tags, document types, permissions).
- Create and wire an agent: Build an agent that uses one-click RAG against this Knowledge Base, enforce citation requirements in its response logic, and deploy it via your chosen interface (form, chat, or embedded workflow).
What’s the difference between ingesting PDFs directly and syncing from SharePoint?
Short Answer: Direct PDF ingestion is ideal for static or batch uploads, while SharePoint sync keeps your Knowledge Base aligned with ongoing document changes and permissions.
Expanded Explanation:
Direct PDF upload is straightforward: you drop files into StackAI (or connected storage), and the platform handles OCR, parsing, and indexing. It’s best when you’re onboarding a one-off archive (e.g., historical contracts, legacy SOP binders, prior RFPs). SharePoint sync, on the other hand, is a continuous pipeline. It respects how your organization already stores, versions, and secures documents. When a policy is updated in SharePoint, the associated Knowledge Base can be re-indexed so agents always answer from the latest version.
From a governance standpoint, SharePoint sync is better aligned with enterprise practices. It lets you use existing access control, retention, and review workflows, rather than duplicating document management inside another system. Many teams use both: an initial bulk upload from PDFs plus ongoing SharePoint sync for living documents.
Comparison Snapshot:
- Option A: Direct PDF ingestion: Fast for bulk loads and static archives; simple but not automatically kept in sync as files change elsewhere.
- Option B: SharePoint sync: Continuous and aligned with existing permissions and versioning; ideal for living policies, SOPs, and team spaces.
- Best for: Enterprise IT stacks where SharePoint is the system of record for current documents, supplemented by one-off PDF uploads for legacy or external content.
How do we require that every agent answer includes citations?
Short Answer: Configure your agent to use StackAI’s Knowledge Retrieval (RAG) and enforce response templates or policies that include citations tied to the retrieved documents.
Expanded Explanation:
In practice, you want the agent to do three things: (1) retrieve the most relevant passages from your Knowledge Base, (2) generate an answer that stays within those passages, and (3) attach clear citations—such as document titles, sections, URLs, or IDs—so users can verify the answer. StackAI’s one-click RAG is designed for this: the agent first performs retrieval over the indexed SharePoint/PDF content, then passes both the question and retrieved context into the model with instructions to include citations.
On the configuration side, you can make citations a hard requirement through system prompts, response schemas, or guardrails. For example, you can define that every answer must list the underlying documents and optionally the snippet or page number used. You can also log which sources were retrieved and cited, which becomes part of your audit trail and helps you review accuracy in production.
What You Need:
- A RAG-enabled agent configured to query your StackAI Knowledge Base.
- Response policies or templates that mandate citations (document names, links, IDs, and/or page or section references) in every answer.
How does this setup support governance, security, and enterprise rollout?
Short Answer: By centralizing content in a governed Knowledge Base, enforcing cited answers with RAG, and deploying on StackAI’s secure, enterprise-grade platform, you get verifiable responses, audit trails, and deployment options that match your security posture.
Expanded Explanation:
For IT and Enterprise Architecture teams, the goal isn’t just to “search PDFs” but to enable governed, auditable AI usage across claim processing, IT ticket triage, support desks, due diligence, and RFP drafting. StackAI is built as an Enterprise AI Transformation Platform: you can deploy multi-tenant, in your VPC, or on-premise, while maintaining feature controls, audit logs, and publishing workflows that feel like software delivery. Every agent run can be traced—what documents were retrieved, what prompt was used, what the model responded with—so you can prove how an answer was produced.
On the security front, StackAI backs its claims with certifications like HIPAA, GDPR, SOC 2 Type II, and ISO 27001, and it explicitly states that customer data is not used to train AI models. Data sent to third-party models or integrations is handled under transparent DPAs and opt-out controls. Combined with 100+ enterprise integrations, this means agents can read, write, and execute tasks across your systems while staying inside your security and compliance boundaries.
Why It Matters:
- Risk-managed rollout: Cited answers, audit logs, and environment control help security and compliance teams sign off on AI agents in regulated operations.
- Path from pilot to production: With telemetry (runs, users, errors, tokens) and controlled publishing, you can start small, measure reliability, and scale agentic workflows across departments without losing governance.
Quick Recap
To build a StackAI Knowledge Base from SharePoint and PDFs and require citations in answers, you (1) connect SharePoint and upload or sync your PDFs, (2) let StackAI’s OCR and indexing pipeline turn them into a unified, searchable Knowledge Base, and (3) attach that Knowledge Base to a RAG-enabled agent configured to always return cited answers. This gives your teams a governed way to query policies, procedures, and reference docs, with enterprise-grade security, clear provenance for every response, and a path to scale agentic workflows beyond experiments into production.