Use
Copilot on the knowledge you already have
When your knowledge already lives in Microsoft 365 and SharePoint, Copilot with proper permissions and tidy sources answers a large share of everyday questions. Test that before buying anything.
Give your team one place to ask how the business works.
A reliable assistant that finds the right source across SharePoint, folders, manuals and policies — and shows where the answer came from.
Can we build an AI assistant on our internal company knowledge?
Yes. Existing Microsoft, Salesforce and specialist search platforms can already answer questions across controlled company knowledge sources. The key issues are not the chatbot itself but source quality, permissions, freshness and whether the answer needs only information or also access to operational systems.
The answer exists. Finding it is the job.
The knowledge is written down — somewhere:
- procedures in SharePoint, in three versions
- product knowledge in manuals and old proposals
- decisions in Teams threads and meeting notes
- policy answers that only two colleagues actually know
- project files organised by whoever left last year
So people ask each other, interrupt the expert, or act on the outdated version.
Use · Extend · Buy · Build
Native capability is most often sufficient here — exactly why independent advice matters.
- 1
Use
Native capability
- 2
Extend
Connect the missing pieces
- 3
Buy
Specialist solution
- 4
Build
Own the differentiator
Extend
The answer spans documents and systems
Real questions often need both a document and a system: the policy plus this customer's contract in CRM, the manual plus the machine's service history in ERP. Connecting those sources is where the assistant becomes an operational tool.
Buy
Retrieval quality is the bottleneck
Enterprise search and knowledge specialists earn their place when sources are highly fragmented, retrieval quality is the main challenge, and advanced governance and search are already productised.
Build
From finding answers to making calls
Build when the assistant must reason, not just retrieve: not “What does policy X say?” but “Given this customer, contract and exception history, what should we do?” That moves from knowledge retrieval toward operational intelligence — and can be worth owning.
In practice
A question, answered with its source
The pattern that builds trust in the answers:
- 1
An employee asks in plain language
“What's our returns policy for B2B customers in Germany?” — in Teams, or wherever they work.
- 2
The assistant finds the right sources
Only in content this employee is allowed to see — permissions are inherited, not rebuilt.
- 3
It answers and cites
A direct answer with links to the exact policy section it came from.
- 4
Stale content gets flagged
Contradicting or outdated sources surface instead of silently winning.
- 5
Gaps become visible
Questions without a good source tell you exactly which knowledge to write down next.
What should we measure?
No promised percentages. We agree the baseline, then measure:
- time to answer
- search abandonment
- answer and citation accuracy
- repeated questions to experts
- active adoption
We don't force a strategy project in front of an obvious solution.
If the route is clear
Straight to configuration or implementation with your partner, a specialist product or the right team.
If the route is uncertain
We compare the options or validate the workflow with a Minimal Viable Agent first.
If several opportunities compete
We prioritise them through a ScopeRight Scoping Workshop.
Works with the stack you already have
We start from your current CRM, ERP, email, documents and SaaS — not from a new platform.
Frequently asked questions
Is Microsoft 365 Copilot enough for this?
Often, yes — when your knowledge lives in Microsoft 365, permissions are right and sources are reasonably tidy. That's the first thing we test, because it means no new software.
How do we stop the assistant from inventing answers?
Restrict it to controlled sources, require citations, and make “I can't find this” an acceptable answer. Grounded retrieval with visible sources is the standard pattern.
What about permissions and confidential documents?
The assistant must inherit your existing access rights, so nobody gets an answer from a document they couldn't open themselves. This is a hard requirement, not a feature.
Our documentation is outdated. Should we fix that first?
Start with the domains where sources are decent, and use the assistant's unanswered questions to prioritise what to fix. A cleanup project without usage data tends to clean the wrong things.
When would we need more than search?
When answers require reasoning over your own rules and history — combining a policy, a contract and past exceptions into a recommendation. That's a build decision, and it should be a deliberate one.
Where this fits
Every service works on its own. Unsure where to start? Begin with the free intake.
Accelerate AI on your existing enterprise platform
Get more from Microsoft, Salesforce or SAP before adding another AI stack.
Validate a use case with a Minimal Viable Agent
Evidence before scale: validate one use case end to end.
Take a validated use case into operation
Deploy, configure or build — the architecture follows the scope.
Explore the AI Field Sprint
Find the AI workflows worth deploying — inside the business.
Need structure before you spend more on AI?
One call. Clear priorities and a recommended path.