AI Automation Testing Tool for Dynamics 365
Nocode test automation for Dynamics 365, authored in plain English by functional experts.
DynaTech’s AI Automation Testing Tool is a purpose-built accelerator designed to transform Dynamics 365 test automation from a technical bottleneck into a business-owned capability. Functional consultants and QA teams can create, execute, and maintain automated test cases written in plain English while the platform intelligently handles execution, UI changes, and reporting.
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Why Traditional Test Automation Breaks in Dynamics 365
Dynamics 365 environment changes on a constant note. Monthly Microsoft releases, ISV solutions, custom extensions, and Power Platform integrations introduce frequent UI and workflow changes. Traditional automation frameworks struggle to keep pace. This turns automation into a maintenance burden instead of a productivity advantage.
Organizations attempting D365 test automation often encounter recurring challenges:
- Heavy reliance on technical scripting specialists
- Selector-based automation that fails after UI updates
- Continuous effort required to repair broken test scripts
- Slower regression testing and delayed UAT cycles
- Security concerns when handling credentials and test data
The result is less automation and lower confidence during every release cycle.

AI Automation Testing Tool - A D365 Accelerator
DynaTech’s AI Automation Testing Tool is a custom-built Dynamics 365 Automation Testing Tool engineered for complex enterprise environments running Dynamics 365. Unlike generic automation platforms, this accelerator is designed specifically to align with the architecture, release cadence, and customization depth of modern D365 ecosystems.
Business workflows are authored in plain English by functional experts, while the platform intelligently interprets intent, executes scenarios, and continuously maintains automation through AI.
As a true no code test automation platform, it redefines ownership of Dynamics 365 Test Automation by enabling functional and QA teams to create and sustain automation at scale, while maintaining the reliability and security standards expected in enterprise deployments.
How the AI Automation Testing Tool Works
The platform combines natural language understanding, AI reasoning, and enterprise-grade automation execution into a unified enterprise test automation platform purpose-built for Dynamics 365.
Process Flow
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Test cases are authored in plain English by functional experts
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Requests are processed through Azure AI Foundry and interpreted by enterprise LLMs
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Playwright MCP converts AI intent into executable virtual user actions
- Test steps are executed on real browsers (Chrome, Edge, Firefox)
- Execution outcomes are captured and delivered as test results and insights
This approach enables plain English Test Automation while ensuring reliable and repeatable Dynamics 365 Regression Automation.

Key Capabilities of DynaTech’s AI Automation Testing Accelerator
- Natural Language Test Authoring
- Self-Healing AI Engine (3-Tier Memory)
- Complete Virtual User Automation
- Parameterized and Data-Driven Testing
- Analytics and Execution Insights
- Enterprise-Grade Security and Deployment
Natural Language Test Authoring
Create automated test scenarios using plain English for functional and QA teams get the benefits of automation without coding dependencies. This enables scalable AI driven test automation across Dynamics 365 business processes.
What this enables:
• Test creation without scripts or automation frameworks
• Faster onboarding for functional consultants and QA teams
• Reduced dependency on technical automation specialists
• Scalable automation across business workflows
Self-Healing AI Engine (3-Tier Memory)
Automation continuously adapts to UI and workflow changes using contextual recognition instead of static selectors. This ensures stable and reliable regression testing Dynamics 365 even after platform updates.
What this enables:
• Automatic adaptation to Dynamics 365 UI changes
• Reduced effort spent fixing broken test cases
• Higher automation stability across releases
• Long-term sustainability of automation investments
Complete Virtual User Automation
Built on Playwright with 22+ MCP tools, the platform replicates real user behavior across browsers to deliver reliable Dynamics 365 test automation execution.
What this enables:
• Click and keyboard interactions
• Form validation and submission workflows
• File upload and download automation
• Drag-and-drop operations and dialog handling
• Cross-browser execution across Chrome, Edge, and Firefox
Parameterized and Data-Driven Testing
Execute the same test scenarios across multiple datasets, legal entities, and regions to support enterprise-scale D365 test automation.
What this enables:• Multi-entity and multi-region test execution
• Reusable test scenarios across environments
• Expanded automation coverage without duplication
• Faster validation for global deployments
Analytics and Execution Insights
Real-time dashboards provide visibility into execution trends, stability, and automation to improve testing maturity.
What this enables:
• Insight into execution success and failure trends
• Measurement of automation growth
• Identification of stability and risk areas
• Visibility into automation ROI and performance
Enterprise-Grade Security and Deployment
Security is embedded across the platform, making this a trusted AI automation testing tool for enterprise environments.
What this enables:
• Fernet encryption for credentials and test data
• JWT-based authentication and access control
• Ephemeral Docker-based isolated execution
• Bring-Your-Own-Key (BYOK) support for Azure OpenAI and private AI Foundry
• Multi-LLM compatibility including Azure OpenAI, Anthropic, and Gemini
Natural Language Test Authoring
Create automated test scenarios using plain English for functional and QA teams get the benefits of automation without coding dependencies. This enables scalable AI driven test automation across Dynamics 365 business processes.
What this enables:
• Test creation without scripts or automation frameworks
• Faster onboarding for functional consultants and QA teams
• Reduced dependency on technical automation specialists
• Scalable automation across business workflows
Self-Healing AI Engine (3-Tier Memory)
Automation continuously adapts to UI and workflow changes using contextual recognition instead of static selectors. This ensures stable and reliable regression testing Dynamics 365 even after platform updates.
What this enables:
• Automatic adaptation to Dynamics 365 UI changes
• Reduced effort spent fixing broken test cases
• Higher automation stability across releases
• Long-term sustainability of automation investments
Complete Virtual User Automation
Built on Playwright with 22+ MCP tools, the platform replicates real user behavior across browsers to deliver reliable Dynamics 365 test automation execution.
What this enables:
• Click and keyboard interactions
• Form validation and submission workflows
• File upload and download automation
• Drag-and-drop operations and dialog handling
• Cross-browser execution across Chrome, Edge, and Firefox
Parameterized and Data-Driven Testing
Execute the same test scenarios across multiple datasets, legal entities, and regions to support enterprise-scale D365 test automation.
What this enables:• Multi-entity and multi-region test execution
• Reusable test scenarios across environments
• Expanded automation coverage without duplication
• Faster validation for global deployments
Analytics and Execution Insights
Real-time dashboards provide visibility into execution trends, stability, and automation to improve testing maturity.
What this enables:
• Insight into execution success and failure trends
• Measurement of automation growth
• Identification of stability and risk areas
• Visibility into automation ROI and performance
Enterprise-Grade Security and Deployment
Security is embedded across the platform, making this a trusted AI automation testing tool for enterprise environments.
What this enables:
• Fernet encryption for credentials and test data
• JWT-based authentication and access control
• Ephemeral Docker-based isolated execution
• Bring-Your-Own-Key (BYOK) support for Azure OpenAI and private AI Foundry
• Multi-LLM compatibility including Azure OpenAI, Anthropic, and Gemini
Implementation & Onboarding Approach
Our deployment is structured to accelerate value while aligning with enterprise IT and security policies.
End-to-end Onboarding Journey
- Environment setup and secure configuration
- Deployment aligned with enterprise governance standards
- Enablement sessions for functional and QA teams
- Initial automation coverage creation
- Post-go-live hypercare support
Organizations begin seeing measurable automation advantages within weeks.
Accelerate Your Dynamics 365 Releases with AI-Driven Test Automation
Turn every Dynamics 365 update into a confident release with AI-driven Dynamics 365 test automation.
Who Should Use This Accelerator
Dynamics 365 Functional Consultants
Enable functional teams to embrace automation without coding dependencies.
QA & Test Managers
Expand coverage, reduce manual effort, and gain visibility into testing maturity.
Enterprises with Frequent D365 Releases
Ensure stable regression cycles despite continuous platform updates.
Organizations Scaling Without Expanding QA Teams
Increase testing capacity without increasing headcount and costs.
Why Enterprises Choose DynaTech
DynaTech brings the right blend of technical depth, industry experience, and Microsoft Fabric expertise to help enterprises deploy AI that works in the real world.
What Sets Us Apart
Proven expertise in Microsoft Fabric & Dynamics 365
Deep capability across Fabric workloads, OneLake, Lakehouse, Azure services, and the full Dynamics ecosystem.Market‑ready AI use cases — not experiments
Pre‑built, production‑ready AI solutions designed for real business functions and industry operations.Built‑in governance, security & scalability
Every implementation follows Microsoft’s data governance framework to ensure responsible, enterprise‑grade AI.
Seamless integration with managed services
Continuous monitoring, optimization, and Fabric platform management to keep AI running at peak performance.Cross‑industry AI experience
Proven success delivering AI for healthcare, manufacturing, distribution, nonprofits, and project‑driven organizations.
Proven expertise in Microsoft Fabric & Dynamics 365
Deep capability across Fabric workloads, OneLake, Lakehouse, Azure services, and the full Dynamics ecosystem.Market‑ready AI use cases — not experiments
Pre‑built, production‑ready AI solutions designed for real business functions and industry operations.Built‑in governance, security & scalability
Every implementation follows Microsoft’s data governance framework to ensure responsible, enterprise‑grade AI.
Seamless integration with managed services
Continuous monitoring, optimization, and Fabric platform management to keep AI running at peak performance.Cross‑industry AI experience
Proven success delivering AI for healthcare, manufacturing, distribution, nonprofits, and project‑driven organizations.
Business Impact
Organizations adopting this AI test automation for Dynamics 365 experience measurable outcomes across release cycles:
- Automation maintenance reduced from days to minutes
- Regression coverage expanded without increasing QA resources
- Business users empowered due to automation workflows
- Higher confidence during Microsoft and ISV updates
- Faster release cycles and improved deployment quality
The result is a sustainable, scalable approach to Dynamics 365 regression automation.
AI Use Cases by Business Function
AI for Dynamics 365 (Sales, CRM, Finance & Operations)
AI for Dynamics 365 (Sales, CRM, Finance & Operations)
Predictive Sales & Pipeline Intelligence
Challenge: Uncertain forecasts and reactive sales planning
AI Approach: Models examine historical CRM data, pipeline velocity, buyer behavior & deal patterns
Fabric Components: Data Factory · Lakehouse · Analytics workloads
Impact: Higher forecast accuracy, smarter prioritization, elevated win rates
Intelligent Demand & Inventory Forecasting
Challenge: Stockouts, overstocking, and planning inefficiencies
AI Approach: Demand models trained on transactional, seasonal & external datasets
Fabric Components: OneLake · Medallion Architecture · AI workloads
Impact: Low inventory costs, optimized supply chain, better planning accuracy
See AI in Action — Powered by Microsoft Fabric
- Finance & Operations Copilot Agent
- Sales Order Creation Agent
- SmartERP Agent
- D365 Configuration Test Generator
- License Optimization Agent
- D365 Support Ticket Agent
- D365 Support Ticket Agent for Sales Hub
- Sales Pipeline Email Accelerator
- Sales QnA Agent
- Purchase Requisition (PR) Agent
- Shipping Services QnA Bot
- Lead to Cash AI Test Automation
- Case to Resolution AI Test Automation
- Field Service AI Test Automation
- O2C AI Test Automation
- P2P AI Test Automation
- R2R Financial Close AI Test Automation
- Inventory & Warehouse AI Test Automation
Predictive Issue Detection
Historical incident data and system behavior are continuously analyzed to identify early risk indicators. This enables intervention before performance degradation or service disruption occurs.
Business impact
- Reduced Downtime
- Proactive Risk Mitigation
- More Stable Operations
AI‑Driven Performance Insights
System telemetry and workload patterns are analyzed to highlight inefficiencies and performance constraints. Insights are used to guide targeted optimization and capacity planning initiatives.
Business impact
- Improved System Responsiveness
- Optimized Infrastructure Utilization
- Data‑driven Planning Decisions
Controlled. Secure. Accountable.
AI is used within defined boundaries, aligned with security, compliance, and operational governance requirements. This ensures measurable improvement without introducing operational or compliance risk.
Business impact
- Strengthened Data Security & Access Control
- Reduced Compliance & Operational Risks
- Consistent Governance with Automated Controls
AI for Dynamics 365 (Sales, CRM, Finance & Operations)
AI for Dynamics 365 (Sales, CRM, Finance & Operations)
Predictive Sales & Pipeline Intelligence
Challenge: Uncertain forecasts and reactive sales planning
AI Approach: Models examine historical CRM data, pipeline velocity, buyer behavior & deal patterns
Fabric Components: Data Factory · Lakehouse · Analytics workloads
Impact: Higher forecast accuracy, smarter prioritization, elevated win rates
Intelligent Demand & Inventory Forecasting
Challenge: Stockouts, overstocking, and planning inefficiencies
AI Approach: Demand models trained on transactional, seasonal & external datasets
Fabric Components: OneLake · Medallion Architecture · AI workloads
Impact: Low inventory costs, optimized supply chain, better planning accuracy
See AI in Action — Powered by Microsoft Fabric
- Finance & Operations Copilot Agent
- Sales Order Creation Agent
- SmartERP Agent
- D365 Configuration Test Generator
- License Optimization Agent
- D365 Support Ticket Agent
- D365 Support Ticket Agent for Sales Hub
- Sales Pipeline Email Accelerator
- Sales QnA Agent
- Purchase Requisition (PR) Agent
- Shipping Services QnA Bot
- Lead to Cash AI Test Automation
- Case to Resolution AI Test Automation
- Field Service AI Test Automation
- O2C AI Test Automation
- P2P AI Test Automation
- R2R Financial Close AI Test Automation
- Inventory & Warehouse AI Test Automation
Predictive Issue Detection
Historical incident data and system behavior are continuously analyzed to identify early risk indicators. This enables intervention before performance degradation or service disruption occurs.
Business impact
- Reduced Downtime
- Proactive Risk Mitigation
- More Stable Operations
AI‑Driven Performance Insights
System telemetry and workload patterns are analyzed to highlight inefficiencies and performance constraints. Insights are used to guide targeted optimization and capacity planning initiatives.
Business impact
- Improved System Responsiveness
- Optimized Infrastructure Utilization
- Data‑driven Planning Decisions
Controlled. Secure. Accountable.
AI is used within defined boundaries, aligned with security, compliance, and operational governance requirements. This ensures measurable improvement without introducing operational or compliance risk.
Business impact
- Strengthened Data Security & Access Control
- Reduced Compliance & Operational Risks
- Consistent Governance with Automated Controls
Industry‑Focused Managed Services & Accelerators
DynaTech delivers industry‑aligned Dynamics 365 managed services supported by prebuilt accelerators and domain‑specific best practices. These accelerators are designed to improve operational performance, reduce platform risk, and accelerate value realization, while remaining fully governed within our managed services framework.
Manufacturing
Production Optimization & Quality Intelligence
Challenge: Unplanned downtime, inconsistent quality, limited production visibility
AI Approach: Analyze sensor data, production logs & quality records to detect anomalies, predict failures, and optimize parameters in near real time
Fabric Components: Data ingestion pipelines · OneLake · Lakehouse · Analytics workloads
Impact: Lower downtime, better quality, higher throughput, reduced manufacturing costs
See AI in Action — Powered by Microsoft Fabric
- Packaging Quality Control
- Pharmaceutical Quality Inspection
- Circuit Diagram Vision System
- Electrical Circuit Analyzer
- Dispatch Gate Management
Logistic Dispatch Automation
Healthcare
Patient Operations & Resource Optimization
Challenge: Inefficient patient flow and uneven utilization of clinical resources
AI Approach: Use historical volumes, staffing patterns & operational data to optimize scheduling, bed allocation & capacity planning
Fabric Components: Data ingestion pipelines · Lakehouse · Analytics workloads
Impact: Faster patient flow, optimized staffing, improved experiences, better operational efficiency
See AI in Action — Powered by Microsoft Fabric
- Health Chat Concierge
- Clinical Documentation & Conversation AI
- Clinical Notes Enrichment
- AI Driven Nutrition Planning
- Early Dementia Detection
Members & Associations (Non‑Profit)
Member Engagement & Impact Analytics
Challenge: Fragmented member data and manual impact reporting
AI Approach: Unify membership, engagement & program data to analyze patterns, predict churn, and surface impact insights
Fabric Components: Data ingestion pipelines · OneLake · Lakehouse · Analytics workloads
Impact: Higher retention, stronger engagement strategies, quicker reporting, improved impact visibility
See AI in Action — Powered by Microsoft Fabric
- Enterprise Sentiment Classifier
- Product Review Intelligence
- Customer Service Response Automation
Wholesale & Distribution
Demand Forecasting & Inventory Optimization
Challenge: Inaccurate forecasts, excess inventory, stockouts
AI Approach: AI models analyze sales history, seasonality & supply chain inputs to forecast demand and optimize replenishment
Fabric Components: Data ingestion pipelines · Lakehouse · Analytics workloads
Impact: Lower inventory costs, better fulfillment rates, improved demand visibility, higher efficiency
See AI in Action — Powered by Microsoft Fabric
- Inventory & Warehouse AI Test Automation
- Demand-related:
- Intelligent Sales Forecasting
- Claims Data Analyzer
Project Services
Project Performance & Resource Optimization
Challenge: Margin leakage, poor resource utilization, limited project visibility
AI Approach: Analyze timelines, resource usage, cost data & delivery history to predict risks and optimize staffing
Fabric Components: Data ingestion pipelines · OneLake · Lakehouse · Analytics workloads
Impact: Better margins, optimized resources, predictable delivery, stronger client satisfaction
See AI in Action — Powered by Microsoft Fabric
- Workforce Productivity Analyzer (cross-functional but fits here)
- Timesheet Suggestion Agent
- Personal Secretary Agent
Manufacturing
Healthcare
Members & Associations (Non‑Profit)
Wholesale & Distribution
Project Services
Azure Data & Microsoft Fabric Services
What We Do
- Implement Microsoft Fabric on Azure
- Design lakehouse and data warehouse architectures
- Build data pipelines and Power BI analytics
- Migrate Azure Synapse workloads to Fabric
Outcomes
- Faster analytics delivery
- Lower analytics operating cost
- Scalable enterprise data platform
Data Warehouse & Lakehouse Modernization
What We Do
- Modernize legacy data warehouses
- Design lakehouse architectures on Azure
- Implement cloud and hybrid data platforms
- Optimize performance and cost
Outcomes
- Scalable modern analytics
- Reduced infrastructure cost
- AI-ready data pipelines
MDM / CDM & Data Governance
What We Do
- Implement Master Data Management (MDM)
- Define Common Data Models (CDM)
- Establish data governance frameworks
- Enable metadata, lineage, and data quality
Outcomes
- Single, consistent source of data
- Trusted analytics and reporting
- Compliance and audit readiness
AI-Ready Data Platforms & AI Agents
What We Do
- Design AI-optimized data architectures
- Build semantic layers for AI consumption
- Enable agent-ready data pipelines
- Prepare data foundations for Copilot and AI agents
Outcomes
- Reliable AI insights
- Intelligent automation
- Scalable AI adoption
Azure Data & Microsoft Fabric Services
What We Do
- Implement Microsoft Fabric on Azure
- Design lakehouse and data warehouse architectures
- Build data pipelines and Power BI analytics
- Migrate Azure Synapse workloads to Fabric
Outcomes
- Faster analytics delivery
- Lower analytics operating cost
- Scalable enterprise data platform
Data Warehouse & Lakehouse Modernization
What We Do
- Modernize legacy data warehouses
- Design lakehouse architectures on Azure
- Implement cloud and hybrid data platforms
- Optimize performance and cost
Outcomes
- Scalable modern analytics
- Reduced infrastructure cost
- AI-ready data pipelines
MDM / CDM & Data Governance
What We Do
- Implement Master Data Management (MDM)
- Define Common Data Models (CDM)
- Establish data governance frameworks
- Enable metadata, lineage, and data quality
Outcomes
- Single, consistent source of data
- Trusted analytics and reporting
- Compliance and audit readiness
AI-Ready Data Platforms & AI Agents
What We Do
- Design AI-optimized data architectures
- Build semantic layers for AI consumption
- Enable agent-ready data pipelines
- Prepare data foundations for Copilot and AI agents
Outcomes
- Reliable AI insights
- Intelligent automation
- Scalable AI adoption