Three Copilots, three jobs,
one operations workflow.
Copilot consultant for industrial operations. M365 Copilot for the Operations Director's inbox. Power BI Copilot for plant-manager questions in plain English. Copilot Studio for custom agents that write back to your systems. We name which one fits which workflow before we build.
Who this is for
Copilot built around your role
Copilot consulting for manufacturing, FMCG and supply chain teams — the workflow each leader owns, and the grounded agent that answers it without inventing a number.
Operations Director
The problem
Someone switched Power BI Copilot on over a semantic model nobody governed, so it answers the morning-huddle questions confidently — and often wrong. Now the room trusts it less than the spreadsheet it replaced.
What we build
Power BI Copilot and Copilot Studio grounded on a governed Microsoft Fabric semantic model — every OEE, OTIF and fill-rate measure defined once, documented with synonyms, so the answer matches the dashboard.
The morning huddle asks in plain English and trusts the number
IT Head
The problem
Microsoft 365 Copilot went tenant-wide before the sensitivity labels were sorted, so it can surface a confidential file to whoever asks. No Microsoft Purview guardrail sits between the model and the answer.
What we build
A governed rollout — Microsoft Purview labels and DLP checked first, Copilot scoped to governed workspaces, and Entra ID conditional access so exposure is closed before enablement, not after.
Sensitive data stays scoped to who should see it
Head of Data
The problem
The business wants Copilot on everything, but the underlying model has measures named Measure 1 to Measure 40 and no owner, so grounding is a fiction and every answer is a guess.
What we build
A hardened Power BI semantic model on Microsoft Fabric — measures named for the business term, synonyms and example questions documented, a named owner — the grounding layer Copilot Studio actually needs.
One governed model Copilot can answer from
Line Manager
The problem
Your team fields the same questions all shift — where is OEE on Line 3, is that order in full — and each one becomes a Teams message to an analyst who is already three deep.
What we build
A Copilot Studio agent grounded on the governed Microsoft Fabric and Power BI model and deployed in Microsoft Teams, scoped to answer that handful of operational questions from live data.
40–60% fewer ad-hoc report requests
The Problem
Patterns we see in every engagement
Microsoft has three Copilots that matter for industrial operations. Most buyers do not know which does what. The vendor pitch blurs them on purpose. We name the differences before we propose.
Vendor pitch promises 'ask anything' — your team needs 'do this one thing reliably'.
The Copilot demo is open-ended. The production workflow is specific. Pilots that fail usually try to do the demo. Pilots that succeed pick one workflow and constrain the agent to do it well.
Hallucination is real — and unconstrained Copilots will produce wrong answers.
Every LLM-powered Copilot will confidently produce wrong answers for ambiguous prompts. The mitigation is not better prompts — it is grounding the agent in your data and constraining what it can answer.
Copilot Studio messaging cost compounds at scale.
At USD 0.0085/message, a heavy agent across 200 users runs USD 1,500–3,500/month. We model the cost before we deploy — not after the first invoice surprise.
Power BI Copilot needs a clean semantic model.
Most Power BI estates have measures named 'Measure 1' through 'Measure 40'. Copilot will not recover from that. We clean the model before we enable Copilot — not the other way around.
What we build
What we build
Five engagement shapes. Each one starts with a workflow that is currently manual, and ends with the user — not their boss — validating the agent.
Copilot Studio agent for an operations workflow
Replaces
The plant manager who sends a Teams message to the analyst asking 'what is OEE on Line 3 yesterday' three times a day.
- Custom agent reads order status from ERP, production from MES, stock from WMS — answers one question
- Multi-turn conversation grounded in your data, not in general knowledge
- Write-back via Power Automate where the workflow needs an action — replenishment PO, quality hold, supplier note
- Deployed in Microsoft Teams where your users already work
Workflow time drops from 8–12 minutes to 30 seconds. Analyst inbox queue shrinks.
Power BI Copilot enablement on a hardened model
Replaces
The Q&A interface in Power BI that nobody uses because every question returns 'I don't know that'.
- Audit existing semantic model — naming, measures, relationships, synonyms
- Harden measures and add Q&A synonyms before Copilot is enabled
- Scope Copilot to governed workspaces — block on un-curated departmental models
- Train plant managers, supply chain leads and CFO on what Copilot is good at and not
Plant managers ask questions in plain English at the morning huddle. Copilot answers correctly because the model is correct.
M365 Copilot rollout (governed)
Replaces
The blanket M365 Copilot deployment that surfaces sensitive content to people who should not see it.
- Purview review of sensitivity labels before Copilot is enabled tenant-wide
- DLP policy alignment so Copilot does not surface labelled-confidential content cross-team
- License sizing per persona — Operations Director (yes), shift operator (probably no)
- Adoption programme — Copilot replaces specific habits, not all of them
M365 Copilot ships safely. Adoption is targeted by role, not blanket. Sensitive content stays scoped.
RAG agent on Azure OpenAI for industrial documents
Replaces
The 47-page SOP PDF nobody opens because finding the changeover procedure for Line 4 takes 12 minutes of skimming.
- Document ingestion via Azure Document Intelligence
- Hybrid search (vector + keyword) in Azure AI Search
- Generation via Azure OpenAI with citation to source PDF page
- Surface via Copilot Studio agent or custom Power App
SOP question gets a 30-second answer with citation. Operators trust the answer because the source is named.
Custom plugins — connect Copilot to your specific systems
Replaces
The 'Copilot is great but it does not see our data' wall most pilots hit.
- Power Platform connectors so Copilot reads from and writes back to your specific systems
- Custom Azure Functions for systems without native connectors
- Tested per integration — confidence threshold before write-back
- Audit logging on every action — every write traceable to user, agent and prompt
Copilot stops being a chat interface and becomes an integration layer. Real workflows automate.
Business outcomes
What changes after Copilot is grounded
The one figure below is from delivered MDI engagements where a governed model sits under Copilot; the capability cards apply to every grounded build.
40–60%
Fewer ad-hoc report requests
Copilot on a governed model
6 weeks
To first working Copilot agent
MDI standard cadence
Copilot answers match the governed Power BI dashboard — one measure, defined once
Microsoft Purview labels and DLP checked before Microsoft 365 Copilot goes tenant-wide
Copilot Studio agents scoped to governed Microsoft Fabric workspaces, not un-curated models
Every answer cited to source, every write-back logged to user, agent and prompt
Copilot Studio write-back through Power Automate — a governed action, not a chat reply
Plant managers ask in plain English at the morning huddle, on Power BI Copilot
How we work
From workflow map to first agent in production in 5–6 weeks
We start with the workflow, not the model. The user — plant manager, customer service rep, CFO — validates the prototype. Their boss does not.
01
Discover — map workflows where Copilot would help
Two weeks. Map 4–6 candidate workflows. Score data readiness for each. Score governance readiness. Pick the one with the highest impact and the lowest risk for prototype.
02
Prototype — one agent, validated by the real user
Two to three weeks. Build one Copilot Studio agent for one workflow. Validate with the actual end-user — not their boss. Measure intervention rate (when the user overrides the agent).
03
Deploy and expand
Three to six weeks for first deploy. Roll out to the named persona. Measure adoption and intervention rate. Expand to adjacent workflows on the same Copilot Studio tenant. Each new agent reuses infrastructure.
Technology stack
Copilot Surfaces
AI Foundation
Orchestration
Grounding Data
Governance
Audit
Why MyData Insights
Why choose MDI for Copilot consulting
We name which Copilot fits
Microsoft 365 Copilot, Power BI Copilot and Copilot Studio do three different jobs. We match the surface to the workflow before we build, so you are not paying for the wrong licence.
Governance before enablement
Microsoft Purview labels, DLP policy and Entra ID conditional access are checked before Copilot is switched on — not patched after it surfaces something it should not.
Grounded, not guessing
Every agent is grounded on a governed Microsoft Fabric or Power BI semantic model with documented measures and synonyms, so answers match the dashboard rather than inventing a number.
Microsoft stack specialists
We build only on the Microsoft stack — Copilot Studio, Power Platform, Azure OpenAI, Microsoft Fabric — so your IT team can support what we hand over.
Cost modelled up front
Copilot Studio messaging bills on consumption. We model the monthly cost against your user count before deployment, so the first invoice holds no surprise.
First agent in six weeks
One Copilot Studio agent grounded and validated by the actual end user in six weeks on a fixed scope — not a workshop deck to review.
Common questions
What buyers ask us
Should we wait for the next Copilot release?
No. The Copilot platform is mature enough for production for operations workflows. Waiting for the next release means the workflow stays manual for another quarter while your competitor does not wait. Build now. Iterate.
Can we use ChatGPT, Claude or Gemini instead?
For Microsoft 365-native workflows and Power BI, the Microsoft Copilots are the right answer because of identity, sensitivity labels and tenant data residency. For everything else, generic LLM agents are valid and we have built them for clients on Azure OpenAI. The boundary is identity and data residency, not model quality.
Will not Copilot replace our analysts?
The analysts who only answer questions a Copilot can answer — yes, eventually, partially. The analysts who diagnose problems, work cross-functionally, and own the semantic model — no, those become more valuable. The Copilot is the leverage, not the replacement.
How much does it cost?
We work in fixed-scope, fixed-fee phases — Discover, Prototype, Deploy — never open-ended time and materials, with a steady-state retainer available for ongoing agent tuning once you are live. The fee is quoted precisely after Discover, once we have seen your workflow complexity and connector count, because those are what actually move the number. What we commit to upfront is the timeline: first working output in 6 weeks, not a 50-slide roadmap. Copilot Studio messaging is a separate Microsoft licence cost, billed on consumption — we model it before we deploy, not after the first invoice.
What about hallucination risk?
Citation to source for every answer (RAG). Confidence threshold before write-back (for action agents). Human evaluation set scored monthly. User feedback loop. We do not promise 100% — we promise the floor and we measure to it.
Engagement
Free Copilot Readiness Review
Thirty minutes with Amit on whether your data is ready for Copilot — is the Power BI semantic model governed enough to ground it, which questions Copilot Studio could answer for your teams, and where the grounding and Microsoft Purview gaps sit. No slides, no obligation.
What you get
- A read of whether your Power BI semantic model is Copilot-ready
- The top questions Copilot Studio could answer for your teams
- A grounding and Microsoft Purview governance gap check
- A 6-week roadmap to your first grounded agent
Ready to move
Book a 30-minute Copilot diagnostic
30 minutes with Amit. No slides. No pitch deck. No obligation to proceed. We walk through your candidate workflows and name which Copilot surface fits each one.