Partner Enablement Workshop

AI-Supported Automation
for Dynamics 365 Demos

Combine Microsoft Learn MCP and Dataverse MCP to research, ground, and build repeatable D365 demo environments — proven on Customer Service & Contact Center.

Marvin Heilemann & Joris Kalz
Frontier Application Consultancy · Enterprise Partner Solution Architects
FRONTIER · DEMO AUTOMATION
01 / 10

Your best people deserve better than boring work

On a typical delivery project, 25% of expert time disappears into tasks that AI + MCP can handle — starting today.

📅 Today — where your team’s time actually goes
Strategic
35%
Delivery
40%
😴 Boring Work
25%
Architecture & Design
Fit-Gap Analysis
Stakeholder Alignment
Sprint Planning
Configuration & Dev
Integrations
Testing & UAT
Status Reports
ADO Updates
Meeting Notes
Deployment Logs
Backlog Grooming
😴 The boring work nobody wants…
📊 Status reports & slide decks
📋 ADO work item updates
📝 Meeting notes & minutes
📄 Release & handover docs
🔄 Sprint board maintenance
📂 Backlog triaging
📦 Deployment coordination logs
🔍 Tracking blockers across tickets
🤖
AI + MCP
handles this
GitHub Copilot
ADO MCP Server
D365 CRM MCP
Copilot Studio
⇓
🚀 Time flows back to real work…
💡 Deeper solution architecture
🎯 More client workshop facilitation
⚡ Faster feature delivery
🔧 More integration testing depth
🧩 Better fit-gap & process design
📈 Higher sprint velocity
✅ With AI + MCP — where your team’s time should go
Strategic
45% ▲ +10%
Delivery
50% ▲ +10%
😴 5%
💡
On a 10-person D365 team, 25% boring work = 2.5 FTEs spending their day on tasks AI can do.
With Azure DevOps MCP, D365 CRM MCP & GitHub Copilot, that time flows back to what your consultants love — and what your clients are actually paying for.
~12%
of total project effort
reclaimed per engagement
FRONTIER · BORING WORK
02 / 10

AI-first toolbelt opportunities

AI-First Consulting integrates AI across every process and engagement — from presales to delivery — for faster, outcome-based delivery and greater efficiency.

Across the engagement lifecycle
🤝 Pre-Sales
Solution scoping, rapid prototyping, personalized demos & quality checks
🚗 Delivery
Configuration, coding, testing & delivery-management automation
🗄️

Dataverse MCP

Rapid data-model exploration for scoping; entity & field configuration assistance directly from the IDE.

Pre-Sales · Delivery
🛠️

Development MCP

Rapid prototyping & solution scoping; accelerated plugin, PCF & Power Automate scaffolding.

Pre-Sales · Delivery
🧪

Playwright Test MCP

Demo-environment quality checks; auto-generated E2E tests for model-driven & canvas apps.

Pre-Sales · Delivery
Enabled by
Microsoft Scout
Copilot Studio
Visual Studio Code
FRONTIER · AI-FIRST TOOLBELT
03 / 10

Frontier Application Consultancy|Approach

Taking an AI-first approach to Application Consultancy revolves around a data-driven approach using Clients, Tools and Knowledge.

Scenarios below are potential use cases, not productized capabilities.
🤝 Pre-Sales
🚗 Delivery (Success By Design)
▶
↗️
Initiate
Get ready to start
🛠️
Implement
👥
Prepare
Deploy
⚙️
Operate
Live
Design
Build
RFP agent
Draft RFP / RFI responses
Personalized customer demo
Based on customer data & public info
Fit gap analysis
Match customer processes with Process Repository
Customer Kickoff
Including Copilot training
Solution Blueprint
Draft, review, evaluate
Task initiation
Populate DevOps from Blueprint
Generate FDD, TDD, IDD
Using workshops & ADO as input
AI-assisted coding
AI-assisted configuration
Using knowledge and MCP
Test plan
With evals defined
Configuration documentation
Generated from application
Data migration
Using Fabric IQ and MCP
Training documentation
Generated from application
Go-Live
Planning & readiness assessment
Ops measurement
Agent that measures batch actions and transactions
⇅
★
Tools | MCP servers
★
Knowledge | Work IQ · Fabric IQ · Foundry IQ
★
Clients | M365 Copilot · GHCP · Copilot Studio
⇅
FRONTIER · APPROACH
04 / 10

Why great D365 demos are hard to build

Setting up a credible demo environment is slow, manual, and rarely tailored to the customer in the room.

1–2 wks
To provision & seed a demo
Environment provisioning, sample data, security roles and configuration eat days of specialist time per opportunity.
Generic
Off-the-shelf demo data
Contoso-style datasets rarely reflect the prospect's industry, terminology or processes — so the story doesn't land.
Scarce
Skilled resources
Pre-sales consultants spend on setup the time they should spend crafting a compelling, customer-specific narrative.

What pre-sales teams are telling us

Rebuilding demo data by hand for every prospect and industry vertical.
Environments drift and break between demos — constant re-work before each meeting.
Hard to reflect a customer's real processes without deep configuration effort.
No easy way to reset, clone or share a known-good demo baseline.
FRONTIER · THE CHALLENGE
05 / 10

An AI-first way to build demo environments

Agents plus MCP tooling automate provisioning, data generation and configuration — grounded in the customer's context.

Learn · Ground · Build
🎯 Use Case In
Product capabilities researched & a customer scenario described
🚀 Repeatable Demo Out
Grounded story, configuration steps & demo data — captured for reuse
📚

Microsoft Learn MCP

Researches product capabilities, best practices and documentation — building knowledge for a concrete demo or customer use case.

Learn & understand features
🗄️

Dataverse MCP

Analyzes the real environment — which features are enabled, plus the tables, fields and relationships that already exist.

Ground truth from the tenant
🧠

LLM-Wiki & agents

An agents.md-driven knowledge base keeps use cases, config and demo data structured — so agents can execute repeatably.

Structured, reusable knowledge
FRONTIER · THE SOLUTION
06 / 10

Five building blocks, one workflow

Research the capability, ground it in the real environment, build the story, structure the knowledge, then automate.

1
📚

Research & learn

Explore product capabilities, best practices & docs before building a new use case.

Microsoft Learn MCP
2
🗄️

Ground in Dataverse

Analyze enabled features and the existing tables, fields & relationships in the tenant.

Dataverse MCP
3
🎭

Build the demo story

Personas, business value, storyline, config steps, naming conventions & demo data.

Copilot authoring
4
🧠

Structure the knowledge

Capture it in an LLM-Wiki guided by agents.md so it stays consistent & reusable.

LLM-Wiki · agents.md
5
⚙️

Automate execution

Agent skills + MCP servers apply the configuration and seed the demo environment.

Agent skills · MCP
🔁
Repeatable by design. Once the LLM-Wiki structure exists, multiple use cases build on it — so demo environments for presales become faster to create and repeatable, not one-off manual work.
FRONTIER · BUILDING BLOCKS
07 / 10

The LLM-Wiki that makes it repeatable

An agents.md file guides AI agents to store and maintain demo knowledge in a consistent structure.

📄 agents.md
Instructions for the agents: where to write, how to name things, and which templates & standards to follow — so every use case builds on the same foundation.
🗂️

Demo data

Sample records and datasets that make each scenario believable.

🎭

Use cases

Personas, business value and storylines for each demo scenario.

⚙️

Current configuration

The environment's enabled features, tables, fields and relationships.

🔗

Technical dependencies

Solutions, MCP servers and prerequisites a use case relies on.

📋

Templates & standards

Naming conventions and patterns that keep everything consistent.

FRONTIER · LLM-WIKI
08 / 10

Faster demos, sharper stories, more wins

Reclaim pre-sales capacity and put a tailored, credible environment in front of every prospect.

Hours
From brief to demo-ready — automated provisioning and seeding replace days of manual setup.
Per deal
Industry-tailored data so every demo reflects the prospect's world, not generic sample records.
1-click
Reset & clone a known-good baseline — no more drift or last-minute repair before a meeting.
More time
Back to selling — consultants focus on the narrative and the customer, not the setup.

Demo Setup Effort — Before vs. After

Manual setup1–2 weeks
⏳ baseline
AI-supportedHours
▼ faster
Illustrative — actual time varies by scenario complexity, solution footprint and data volume.
FRONTIER · BUSINESS IMPACT
09 / 10

Make every demo customer-specific

Three moves to make AI-supported demo environments your team's default.

1

Join the partner workshop

See how Microsoft Learn MCP & Dataverse MCP were used for real Customer Service & Contact Center research — and apply the same pattern.

2

Stand up your LLM-Wiki

Adopt the agents.md structure so demo data, use cases, configuration and standards stay consistent and reusable.

3

Automate the next use case

Combine MCP servers and agent skills to build the next presales demo environment — faster, repeatable, and responsibly.

Give every prospect a demo that looks like their own business.
Frontier Application Consultancy · Enterprise Partner Solution Architects
FRONTIER · NEXT STEPS
10 / 10