Copilot knows a lot.
It should know your business.
Microsoft Copilot is only as good as what it can access. ClarityArc builds the RAG pipelines and knowledge architecture that ground Copilot in your verified internal content -- so your people get accurate, permission-aware answers instead of confident guesses.
You bought Copilot. The answers are still wrong.
Microsoft 365 Copilot without proper grounding draws from whatever it can find in your tenant -- including outdated documents, draft files, and content users should not have access to. Garbage in, garbage out at enterprise scale.
SharePoint search was not built for this.
Copilot's default knowledge retrieval relies on SharePoint search -- a keyword-based index that was not designed for semantic AI retrieval. It finds documents that contain the right words. It cannot determine which document actually answers the question.
Your security model has to travel with the answer.
When Copilot retrieves content to answer a question, it needs to respect the same permissions your users have in SharePoint and Teams. Without explicit enforcement at the retrieval layer, users see content they were never meant to access.
Governed knowledge retrieval built for Microsoft Copilot
ClarityArc builds the knowledge layer that sits between your content and Copilot -- a governed RAG pipeline that indexes your approved sources, enforces permissions, and delivers semantically accurate retrieval at query time.
The result is a Copilot that answers from your approved documentation, your current policies, and your active project content -- not from stale files or training data that predates your business.
Source Governance
Approved content from SharePoint, Teams, OneDrive, and connected enterprise systems is classified and ingested into the governed knowledge base
Semantic Indexing
Content is chunked, embedded, and indexed using Azure AI Search with hybrid retrieval -- semantic vector search combined with keyword matching
Permission Enforcement
At query time, retrieval is filtered to content the requesting user is permitted to see -- matching your existing Microsoft 365 permission model
Copilot Grounding
Retrieved content is passed to Copilot as grounding context -- the model synthesizes answers from your content, not from its training data
Source Citations
Every Copilot answer links back to the specific document or SharePoint page it came from -- verifiable and auditable
Built for every Microsoft 365 surface your teams use
Grounded Copilot for the whole organization
Copilot in Word, Excel, Teams, and Outlook grounded in your governed knowledge base. Answers from your actual approved content -- not from Microsoft's general training data or ungoverned SharePoint content.
Custom knowledge agents for specific domains
Purpose-built agents via Copilot Studio targeting specific knowledge domains -- HR policy, field operations, compliance documentation, or customer-facing support. Each agent is scoped, governed, and tested against its specific knowledge set.
AI search embedded where work happens
RAG-powered search embedded directly in SharePoint sites and Teams channels -- employees query their knowledge base in the tools they already use, without switching to a separate AI interface.
Copilot without RAG vs. Copilot with governed retrieval
Draws from all tenant content -- including drafts, outdated documents, and files outside the user's normal scope
No semantic understanding of which document actually answers the question -- returns keyword matches
Permission enforcement happens at the document-access layer only -- not at the retrieval synthesis layer
No audit trail connecting a Copilot answer back to its source documents
Answer quality degrades as content volume grows -- more content means more noise in retrieval
Retrieves only from approved, classified, governed content -- ingestion governance eliminates noise at the source
Semantic vector retrieval finds the content that actually answers the question, not just the one that matches keywords
Per-user access controls enforced at retrieval time -- the answer is built only from content the user is permitted to see
Every answer cites the specific document it came from -- full audit trail for compliance and review
Retrieval accuracy improves as governance improves -- the knowledge base gets better over time, not worse
Four phases from knowledge audit to grounded Copilot in production
Knowledge Audit
We assess your Microsoft 365 environment -- content volume, quality, governance state, and permission model. We identify what should and should not be in the knowledge base before any indexing begins.
Architecture Design
We design the full grounding pipeline -- Azure AI Search configuration, embedding approach, chunking strategy for your document types, permission mapping, and the Copilot or Copilot Studio integration surface.
Build & Test
We build the governed knowledge base, configure the retrieval pipeline, integrate with your chosen Copilot surface, and run structured accuracy testing before any user sees the system.
Deploy & Tune
Production deployment, user rollout, retrieval accuracy monitoring against real queries, and performance tuning until the system meets the quality standard your organization requires.
What Microsoft 365 organizations ask before grounding Copilot
We already have Microsoft 365 Copilot licenses. Do we need additional Azure services?
Yes -- a governed RAG grounding layer requires Azure AI Search for the vector index and Azure OpenAI for the embedding model. Both operate inside your existing Azure tenant, so your data never leaves your environment. The additional Azure service costs are typically $400 to $1,500 per month depending on content volume and query load -- a fraction of the per-user Copilot license spend.
How is this different from Microsoft's own Copilot knowledge connectors?
Microsoft's native connectors index your content and make it available to Copilot, but they do not enforce governance at ingestion, do not provide content-aware chunking, and do not give you control over the retrieval pipeline. ClarityArc builds a purpose-designed retrieval architecture that you control -- with explicit governance decisions, access control enforcement at the retrieval layer, and retrieval quality metrics you can monitor.
Can this work with our on-premises SharePoint content?
Yes. ClarityArc has deployed RAG pipelines that index on-premises SharePoint content via Microsoft Graph connectors and custom sync pipelines. The architecture differs slightly from cloud-native deployments, and we scope the integration approach in Phase 01 based on your specific environment.
What content types does this work with beyond SharePoint documents?
The knowledge base can ingest from SharePoint, Teams channels and chat history, OneDrive, email (with appropriate governance decisions), Azure SQL, Dataverse, and external systems via custom connectors. We scope the source map in Phase 01 and make explicit governance decisions about what should and should not enter the knowledge base before any indexing begins.
How long does it take to get grounded Copilot into production?
A single-domain Copilot grounding project -- one knowledge domain, governed sources, tested and deployed -- typically runs 6 to 10 weeks. Multi-domain or multi-surface deployments take longer. We establish the timeline explicitly in Phase 01 so there are no surprises.
Intelligent Knowledge Systems
View the full practice →You have the Copilot licenses. Let's make them earn their keep.
We start with a focused knowledge audit of your Microsoft 365 environment -- no commitment required beyond that conversation. Bring your Copilot pain points. We will show you exactly what governed grounding fixes.