Knowledge discovery
Select service tickets, approved runbooks, change records, vendor documents and agreed collaboration sources.
Keep the knowledge your team has earnedWhen an engineer leaves,
When an engineer leaves,
the knowledge should stay.
A private knowledge assistant helps engineers find what happened before, why a fix worked and where the evidence lives. We normally begin with retrieval-augmented generation: an existing model connected to selected company knowledge.
Useful fixes are scattered across tickets, documents and conversations. New starters repeat investigations, while the context behind an earlier change can disappear when someone leaves.
Discuss this service →What we can design and deliverA defined scope.
A defined scope.
A useful outcome.
Permission-aware retrieval
Design retrieval to respect source access, tenancy boundaries and the identity of the person asking.
Answers with evidence
Return relevant passages and source links; surface uncertainty and route unanswered questions to a person.
Secret handling
Identify and exclude credentials, sensitive fields and material that should not enter the knowledge index.
Freshness and ownership
Agree document owners, refresh rules, retention and an archive process for obsolete fixes.
Knowledge capture
Draft problem, cause and resolution articles from closed tickets for review before publication.
A controlled workflow
Clear steps. Visible decisions.
- 01Select the sources
- 02Apply permissions and exclusions
- 03Retrieve relevant evidence
- 04Answer with source links
- 05Review and improve
Knowledge owners approve source scope and published guidance. An assistant answer is checked before it becomes a production action; access is never widened simply because material is indexed.
Your delivery pack
What you take away.
- Source inventory and access model
- Ingestion and refresh design
- Search and answer-quality evaluation set
- Pilot assistant with citations
- Knowledge-owner and review workflow
Evidence from the pilot
What we measure.
- Time to find a verified resolution
- Answer accuracy on agreed questions
- Citation relevance and permission checks
- Unanswered or outdated knowledge
Baseline, workload, scope and success criteria are agreed before the pilot. Results and savings are measured, not guaranteed.
Works with your environment.
Options include Microsoft Copilot Studio, Azure AI Search, Amazon Bedrock knowledge bases and a privately hosted retrieval stack. Hosting, model terms, retention and data use are reviewed for the selected design.
View the technology capability map →Connected services
Build the right combination.
AI IT support engineer
Connect trusted IT knowledge, service tools and approved fixes to help your support team resolve repeat issues.
Explore the serviceAI project office
Bring status reporting, actions, risk drafts and change preparation together across the tools your project already uses.
Explore the serviceAI and automation
Join security, IT operations and business workflows with scoped access, tested actions and evidence of what changed.
Explore the serviceHow every product startsOne project or one application, measured in writing
1. ShadowThe AI works beside your team
2. Run approved tasksYour process owner checks the results
3. MeasureHours and cost saved, in writing
Let’s work together
Discuss your project Start with one useful outcome.
Let’s agree the scope, evidence and controls for a focused pilot.