Copilot for Microsoft 365

Boost Productivity & Unlock AI-Powered Insights with Microsoft 365 Copilot

Copilot for Microsoft 365 seamlessly integrates AI with Office apps and Microsoft Graph, leveraging GPT-powered intelligence to generate content and retrieve information instantly. Explore its growing capabilities across Microsoft 365 applications to streamline workflows and enhance efficiency.

Microsoft 365 Copilot transforms the way you work by seamlessly integrating AI-driven intelligence into your favorite Microsoft 365 apps. Designed to enhance efficiency, Copilot helps users draft documents, summarize key information, and respond to inquiries—all within the context of their daily tasks. By delivering real-time, relevant content, it streamlines workflows, improves decision-making, and fosters skill development. Experience a smarter, more intuitive work environment with Microsoft 365 Copilot.

AI Powered Productivity Assistant

 Draft Email Replies in Outlook

Summarize Teams Meetings

Analyse and Explore Excel data

Create PowerPoint drafts with text & images

Services Provided by MDSC1

Our approach to AI with Microsoft 365 Copilot

Robot hand finger pointing, AI technology background

ROI

Define objectives, strategy, and success criteria to measure tangible business value—unlocking a smarter approach to AI with Microsoft 365 Copilot

Risk

Ensure data privacy, security, and responsible AI implementation

Readiness

Ensure data quality, seamless system integration, effective user adoption, governance, and cost management.

Copilot for Microsoft 365 in action by application

Microsoft Word

Scenario: You need to create a detailed report but don’t know where to begin.

How Copilot for Microsoft 354 helps: Copilot in Word pulls data from internal reports, emails, and spreadsheets to create a comprehensive report. It organizes the information, suggests headings, and can even generate conclusions or recommendations based on the content.

Benefits: Save time by automatically generating structured reports, eliminating the need to manually sift through information. Copilot provides a solid starting point, allowing you to focus on fine-tuning the details.

Microsoft Excel

Scenario: You need to analyze a large dataset but are unsure of where to begin.

How Copilot for Microsoft 365 Helps:
Copilot in Excel analyzes your data, suggests relevant charts, and performs advanced calculations like trend analysis or forecasting. It can even generate a summary of the key insights based on the data patterns.

Benefit: Accelerate data analysis by automatically generating insights and visuals, saving hours of manual data manipulation and improving decision-making accuracy.

Microsoft PowerPoint

Scenario: You need to create a compelling presentation but lack design inspiration.

How Copilot for Microsoft 365 Helps: Copilot in PowerPoint suggests slide layouts, designs, and content structure based on the topic or previous presentations. It can generate introductory slides, key points, and even design suggestions to make the presentation visually engaging.

Benefit: Streamline presentation creation with design suggestions, relevant content, and structure—saving you time on formatting and focusing on delivering impactful messages.

Microsoft Teams

Scenario: You need to organize a team meeting but are unsure of the agenda or key topics.

How Copilot for Microsoft 365 Helps: Copilot in Teams analyzes recent conversations and tasks within the group to suggest agenda items. It can also help create a meeting invite, set reminders, and ensure the right team members are notified.

Benefit: Simplify meeting preparation by quickly generating agendas and reminders, allowing you to focus on the discussion rather than the logistics.

Microsoft Outlook

Scenario: You’re overwhelmed with email responses and need to prioritize your next actions.

How Copilot for Microsoft 365 Helps: Copilot in Outlook analyzes your inbox, sorts emails by priority, and even drafts responses for routine inquiries. It can highlight urgent messages and suggest follow-up actions based on previous correspondence.

Benefit: Save time by automating email management, prioritizing responses, and drafting common replies, ensuring you stay on top of your inbox.

Microsoft OneNote

Scenario: You’re preparing for a brainstorming session but have scattered notes across multiple documents.

How Copilot for Microsoft 365 Helps: Copilot in OneNote gathers related information from your files, emails, and meetings, and organizes it into structured notes. It suggests topic categories, helping you quickly focus on the key areas for discussion.

Benefit: Consolidate all relevant notes into a single, organized space, ensuring you’re fully prepared for the session without manually searching through documents.

Microsoft Forms

Scenario: You need to gather feedback for a project but don’t have time to design a survey.

How Copilot for Microsoft 365 Helps: Copilot in Forms suggests survey questions based on your objectives and past feedback forms. It can also help you customize the form design, ensuring it’s aligned with your brand and easy for respondents to complete.

Benefit: Speed up survey creation by automatically generating relevant questions and streamlining form design, allowing you to quickly collect valuable feedback.

Our Engagement Models

Unlock AI-Powered Business Value with Copilot Vision & Value

Identify AI-driven opportunities, build a business case, and develop a strategic roadmap to drive revenue, reduce costs, and enhance employee wellbeing with Microsoft Copilot.

Copilot Vision & Value

Customize & Extend AI with Copilot Studio Vision & Value

Join a one-day workshop to define AI-driven scenarios, build custom agents, and develop a deployment plan—unlocking business value with Microsoft Copilot Studio’s powerful extensibility.

Copilot Studio Vision & Value

Validate AI Impact with Copilot Proof of Value

Helps customers evaluate Microsoft 365 Copilot’s benefits through an Executive Immersion Experience, agent demonstrations, and Copilot Dashboard implementation, showcasing proven scenarios for quick value realization.

Copilot Proof of Value

Accelerate Copilot Deployment & Adoption

Optimize Microsoft Role-based Copilot adoption with expert-led deployment services. Designed for large organizations.


Copilot Role-based Deployment & Adoption Accelerator

Accelerate Copilot Deployment & Adoption at Scale

Tailor your Microsoft Copilot rollout with a modular approach. This engagement supports deployment, drives adoption customized to your business needs.

Copilot Deployment & Adoption Accelerator

How we can help

Showcase real-world value through practical use case scenarios.

Identify key opportunities to leverage Microsoft 365 Copilot in your organization to drive business outcomes and showcase its value.

Security and data

Providing expert security, data, and platform guidance to ensure Copilot is deployed and managed securely and compliantly.



Adoption and change management

Help organizations leverage Microsoft 365 Copilot, foster a data-driven culture, and enhance usability, accessibility, and overall user satisfaction.

Case Study: Citizen Support Agent for Government Services

Challenge

Citizens face challenges in accessing government services efficiently, such as paying fines, applying for schemes, or inquiring about available benefits. Manual processes lead to long wait times and frustration.

The Citizen Support Agent uses AI to provide instant assistance through conversational interfaces. Citizens can inquire about services, pay fines, and apply for schemes using a user-friendly platform. The solution integrates with government databases for real-time updates and provides personalized guidance.

  • Reduced wait times for service-related queries by 60%.
  • Enhanced citizen satisfaction with quick, accurate responses.
  • Increased efficiency for government service teams.

Case Study: Customer Support and Ordering Agent

Challenge

Enterprises struggle to provide consistent customer support and efficient order management, resulting in delayed responses and reduced customer satisfaction.

The AI-powered Customer Support and Ordering Agent integrates with private knowledge bases to resolve queries and facilitate seamless order placement and tracking. The system ensures accurate information retrieval and provides personalized experiences for users.

  • Improved query resolution time by 50%.
  • Enhanced order tracking and delivery processes.
  • Boosted customer loyalty and retention.

Case Study: Sales Copilot for Task Prioritization and Document Generation

Challenge

Sales teams find it difficult to manage multiple opportunities, prioritize daily activities, and generate complex documents like proposals or RFP responses efficiently.

The Sales Copilot provides AI-driven recommendations for task prioritization and automates document generation using customer-specific data. It integrates with CRM systems, enabling sales teams to focus on strategy and client engagement.

  • Increased sales efficiency and productivity by 30%.
  • Faster RFP and proposal turnaround times.
  • Enhanced win rates through streamlined workflows.

Case Study: Marketing Attribution Analysis & Channel Strategy

Challenge

Businesses struggle to determine the effectiveness of their marketing channels, leading to suboptimal budget allocation and wasted spending.

This AI solution delivers advanced attribution models to evaluate campaign performance across channels. It recommends optimal budget allocation and predicts ROI based on historical and real-time data, empowering teams to maximize impact.

  • Increased ROI by 25% through optimized marketing spend.
  • Better understanding of channel performance.
  • Improved campaign effectiveness with data-driven strategies.

Case Study: Employee Attrition Prediction

Challenge

High attrition rates increase hiring costs and disrupt operations for HR teams. Identifying potential attrition risks early is crucial to maintaining workforce stability.

The predictive HR analytics solution uses AI to analyze employee data, survey results, and external factors to forecast attrition risks. It also provides actionable insights for retention strategies, such as personalized engagement programs and benefits adjustments.

  • Reduced employee turnover by 20%.
  • Lower recruitment and onboarding costs.
  • Improved employee morale and productivity.

Case Study: Streamlining HR Operations with GenAI-Powered Automation

Challenge

HR teams faced inefficiencies in creating job descriptions, employment contracts, and offer letters manually, leading to delays. Employees also struggled to access information about HR policies, resulting in repetitive queries and slower response times.

A GenAI agent automated the creation of HR documents using predefined templates and dynamic inputs. The same agent also provided employees with instant, conversational access to information on HR policies, leave balances, and benefits through an AI-powered interface.

  • Reduced document creation time by 70%.
  • Improved employee satisfaction with instant, accurate query resolutions.
  • Ensured document consistency and compliance with organizational standards.
  • Freed HR teams to focus on strategic initiatives.

Case Study: Virtual IT Assistant for First-Level Support

Challenge

IT teams spend excessive time handling repetitive tasks like password resets and troubleshooting simple issues, reducing their ability to focus on critical problems.

The Virtual IT Assistant automates first-level support tasks, offering 24/7 assistance for common queries like login issues or software installation. Complex cases are escalated to human agents with detailed context.

  • Reduced IT support workload by 40%.
  • Faster resolution of routine queries.
  • Improved employee satisfaction with uninterrupted support.

Case Study: ESG Compliance Monitoring & Reporting

Challenge

Organizations struggle with monitoring and reporting ESG metrics due to siloed data and the complexity of regulations, leading to compliance risks.

This AI solution automates ESG data collection, analysis, and reporting. It tracks sustainability, social impact, and governance performance across departments, delivering actionable insights for improved compliance and strategy.

  • Enhanced ESG reporting accuracy by 30%.
  • Streamlined compliance processes.
  • Improved organizational transparency and sustainability initiatives.

Case Study: Procurement Automation

Challenge

Manual procurement processes are time-consuming, error-prone, and fail to meet the agility required for modern businesses.

The AI-based Procurement Automation system streamlines workflows by automating the generation of purchase orders, RFPs, invoices, and PRs. It validates data for compliance and ensures quick approvals.

  • Accelerated procurement cycles by 35%.
  • Reduced errors in document generation.
  • Improved operational efficiency in procurement teams.

Case Study: Predictive Maintenance for Manufacturing Equipment

Challenge

A manufacturing client faced frequent equipment breakdowns, leading to unplanned downtime, high maintenance costs, and delayed production schedules. The customer persona includes operations managers and maintenance teams.

We implemented an AI-powered Predictive Maintenance solution. Using historical machine data, operational parameters, and IoT sensor inputs, the system predicted equipment failures in advance. The solution included advanced anomaly detection, root cause analysis (RCA), and dynamic scheduling of maintenance tasks, ensuring seamless integration into existing workflows.

  • Reduced unplanned downtime by 35%.
  • Decreased maintenance costs by 25%.
  • Improved production efficiency, leading to a 15% increase in throughput.

Case Study: AI Assistant for Legal Document Review

Challenge

Legal teams often spend significant time reviewing large volumes of contracts and legal documents, delaying decision-making processes.

The AI Assistant for Lawyers accelerates document review with intelligent text extraction, clause identification, and risk analysis. It supports multi-language documents, highlights potential compliance issues, and offers automated summaries, enabling lawyers to focus on critical tasks.

  • Reduced document review time by 50%.
  • Increased accuracy in identifying risks and compliance issues.
  • Improved productivity for legal teams by automating routine tasks.

Case Study: Vendor and Bid Selection Using GenAI

Challenge

A procurement team struggled with evaluating multiple vendor proposals efficiently while ensuring compliance and optimal pricing.

The GenAI-powered Procurement Solution analyzes vendor proposals, scores them based on predefined criteria, and identifies the best-fit vendors. It uses natural language processing (NLP) to extract and compare key terms and employs machine learning to recommend optimal bids for projects.

  • Reduced procurement cycle time by 40%.
  • Enhanced decision-making accuracy through unbiased data analysis.
  • Achieved significant cost savings by selecting the most value-adding vendors.

Case Study: Trade and Business Fraud Detection

Challenge

A financial institution faced challenges detecting fraudulent activities in trade and business transactions, leading to reputational and financial risks.

The fraud detection platform uses AI to monitor transaction patterns, identify anomalies, and flag suspicious activities in real time. The solution employs a combination of rule-based engines and machine learning models to adapt to evolving fraud patterns.

  • Reduced fraud-related losses by 30%.
  • Real-time detection of fraudulent transactions, minimizing risk.
  • Improved compliance with regulatory requirements.

Case Study: Credit Risk Underwriting Automation

Challenge

A banking client struggled with manual credit underwriting processes that were time-intensive and prone to human errors, impacting customer onboarding times.

Our AI-driven underwriting solution automates data extraction, scoring, and risk assessment. It integrates multiple data sources, including financial records, credit histories, and market trends, to provide a holistic risk evaluation.

  • Reduced credit processing time by 60%.
  • Increased accuracy in risk assessments, lowering default rates.
  • Enhanced customer satisfaction through faster approvals.