M365 Company Brain

M365 Company Brain for Microsoft-first Teams

Knowledge, routines and decisions live across Teams, SharePoint, Outlook, files and people. AI should help, but access, source quality and operation cannot be lost.

Tirion designs this as a controlled knowledge and operations layer with sources, permissions, review gates and an owner model.

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Concrete use cases

M365 Company Brain for Microsoft-first Teams

Internal knowledge search

Answers from approved M365 sources with citations, uncertainty logic and role-aware access.

Operations routine prep

Recurring service, back-office or reporting work is prepared, prioritized and moved to review.

Account and project briefings

Teams get context from CRM, documents, meetings and project history before work starts.

Architecture solution

Tirion designs this as a controlled knowledge and operations layer with sources, permissions, review gates and an owner model.

The architecture shows where Tirion separates sources, orchestration, AI/agent, human review, target systems and monitoring.

01Sources

SharePoint, Teams, Outlook, OneDrive, CRM, process documents

02Orchestration

Ingestion, permission alignment, retrieval, workflow context

03AI/Agent

Answers, briefings, drafts and routine preparation

04Approval gate

Human review for external, sensitive or operational actions

05Target systems

Teams, CRM, ticketing, reporting, documents

06Monitoring

Source quality, answer quality, adoption, relief, exceptions

Tirion differentiation

M365 Company Brain

The system should never be more powerful than its permission model.
Start with a small trusted source set, not a big-bang knowledge lake.
Operating ownership for knowledge, review and improvement is assigned before launch.

Strong fit when

Microsoft 365 Knowledge & Workflow AI

M365 is the central work surface.
Knowledge search visibly costs time.
Routines repeat, but still need review.

Not a fit if

Not a fit if Microsoft 365 is barely used or no one can own source quality and process review.

Stop/scale rule

Scale only when source quality, permissions, owner model and first relief KPI are stable.

Owner/KPI question

Who owns knowledge quality and who can approve operational answers?

Tirion path

Microsoft 365 Knowledge & Workflow AI

Fits when knowledge and M365 work should become an operating AI layer. If scope is unclear, start with AI Kickstart.

Microsoft 365 Knowledge & Workflow AI

Proof

Anonymized project pattern

SituationAn operations team lost time across reporting, knowledge search and service preparation.

InterventionTirion narrowed 14 routines into a few automation paths with M365 data reality, owner and review boundaries.

Observed resultThe first sprint started with preparation plus human review instead of uncontrolled full automation.

Measurement points

search time reducedanswers with sourcesreview raterecurring routines prepared

Other use cases

Other architecture paths

Governed AI AgentsGoverned AI Agents & Permission Architecture

Agents are expected to use tools, prepare data or trigger workflows. That is where prompt rules stop being enough.

Revenue Ops AIRevenue Ops AI Automation

Sales and account teams lose time in research, routing, follow-up and proposal preparation. Automation cannot lose tone, context or control.

Secure Azure OpenAISecure Azure OpenAI Foundation + AI Cost Control

AI pilots expand, cloud spend spreads and no one consistently owns guardrails, tags, budgets, alerts and scale decisions.

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Should this use case be prioritized with more confidence?

The score classifies whether this path is ready or whether governance, owner, data reality and target state need to be clarified first.

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