The Opportunity
On average, a Support Engineer spends 35-50 minutes every day reviewing their case backlog for prioritization, daily planning, and following up on pending actions. Studies suggest inefficient prioritization and manual follow-ups can increase resolution times by up to 34%.
While Case Summary and Suggested Actions features in DfM offer some support, engineers still need to skim through their bins and open each case at least once daily to utilize these features. There was a clear opportunity to consolidate this fragmented workflow into a single, intelligent experience.
The Solution
SupportIQ uses Generative AI to provide a holistic view of an engineer's bin, addressing three core inefficiencies in a unified platform:
1. AI-Powered Case Prioritization
The system analyzes all active cases and intelligently prioritizes them based on:
- Urgency — SLA timelines, case age, and escalation status
- Support type — break-fix, advisory, and proactive engagement
- Customer sentiment — AI-analyzed tone and frustration indicators from case communications
This eliminates the need for engineers to manually open and scan each case to determine what needs attention first.
2. Automated Follow-ups and Action Plans
For each case, SupportIQ generates:
- Tailored follow-up emails ready for review and send — no more drafting from scratch
- Technical action plans with recommended next steps based on case context and historical patterns
- Proactive reminders ensuring no case falls through the cracks
3. Performance Analytics Dashboard
A real-time dashboard measures and visualizes:
- Time savings per engineer and per team
- Cost savings — assuming a blended cost of $0.50 per minute across chat, phone, and other channels
- Case resolution improvements — tracking the impact of AI-assisted workflows on resolution times
- Operational insights — data-driven analysis of team performance and bottlenecks
Project Overview
In today's fast-paced support environment, managing a heavy workload effectively is crucial for maintaining high levels of customer satisfaction and operational efficiency. SupportIQ harnesses the power of Generative AI to revolutionize the way Support Engineers handle their daily tasks. By analyzing ongoing support cases, our AI solution prioritizes those that require immediate attention and generates tailored action plans for each case. Additionally, it automates follow-up reminders, ensuring timely and consistent communication with customers.
This innovative approach streamlines decision-making, reduces manual task management, and allows Support Engineers to focus on resolving issues more effectively.
Project Goal
To enhance the efficiency of Support Engineers by integrating Generative AI solutions that prioritize support cases, provide customized action plans, and automate follow-up reminders — thereby facilitating faster and more effective issue resolution.
Impact and Results
| Metric | Impact |
|---|---|
| Manual effort saved | ~1 hour per engineer per day |
| Engineer efficiency | 14% increase |
| Operational cost savings | ~$30 per engineer per day |
| Case resolution time | Significant reduction |
| Customer satisfaction | Measurable improvement |
Efficiency calculation: The 14% improvement is derived from the formula: (Minutes Saved / Average DTC in minutes) / Average DTC × Case Volume / 100, demonstrating that even modest time savings per case compound significantly across a full caseload.
Cost impact: At a blended cost of $0.50 per minute to represent variable costs across chat, phone, and other cost variability within LOBs, saving at least 60 minutes per day translates to $30 per engineer per day in operational savings.
Key Benefits
Increased Productivity
By automating manual task management — case scanning, prioritization, and follow-up drafting — Support Engineers can focus more on critical problem-solving activities rather than administrative overhead.
Enhanced Customer Satisfaction
Timely and accurate responses to support cases, driven by AI-generated action plans and automated follow-ups, lead to improved customer experiences and faster issue resolution.
Improved Operational Efficiency
The solution minimizes idle time between case reviews and promotes better case management practices through AI-driven insights and a unified workflow.
Adoption and Recognition
What started as an AppsInfraHack project became a massive success — SupportIQ has been accepted by the Dynamics Engineering Team and is now fully integrated into the DFM Copilot Hub.
Today, more than 11,000 engineers across Microsoft are actively using SupportIQ to prioritize their case backlogs, automate follow-ups, and improve their daily efficiency. The platform continues to deliver measurable impact at scale — saving time, reducing operational costs, and elevating the quality of customer support.
Current Status
SupportIQ is live in production as part of the DFM Copilot Hub, serving 11,000+ Support Engineers across Microsoft's support organization. The solution has proven its value at scale, transitioning from a hackathon prototype to a production-grade tool that is now an integral part of the daily support engineering workflow.