Normalized claim
Productivity: 30%
Up to 30% productivity gains overall.
Near Contact automates operations with AI agents and low-code apps
Use case typeCustomer service automationUpdated Jun 13, 2026
Near Contact implemented Microsoft’s Intelligent Enterprise platform to drive automation, data insights, and AI-driven transformation across its business services operations. The initiative integrated core Microsoft technologies including Dynamics 365, Power Platform (Power Automate, Power Apps, Power BI), Microsoft Dataverse, Copilot Studio, and Azure AI. Real-world implementations span sales, customer service, and field operations, utilizing AI agents for tasks such as lead qualification, sentiment analysis, and predictive maintenance with IoT integration. Automated workflows now handle contract data extraction and operations tasks, while field technicians receive real-time guidance through custom apps. Near Contact reports up to 30% productivity gains, a 20-25% improvement in first-time fix rates for operations, and 15% higher customer service agent productivity. The company credits its competitiveness to both end-to-end automation and democratization of app creation enabled by low-code solutions. A democratized approach empowers business analysts to rapidly innovate, reducing development time and enhancing agility.
- Organization
- Near Contact
- Industry
- Professional Services
- Location
- Global
- Published
- November 2025
Reported outcomes
20-25%
timeTime & speed
30%productivity+15%productivity
Strategic outcomes
Speed & agilityAutomated workflows across business departmentsNew product / capabilityDeployed AI agents for business tasksCustomer experience & trustImproved customer service and field outcomesInnovation & cultureEnabled rapid innovation by business analysts
Catalog median for time & speed deployments: +60% across 143 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Time: 20-25% increase
20–25% improvement in first-time fix rates.
Normalized claim
Productivity: 15% increase
15% increase in customer service agent productivity.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Near Contact
- Provider
- Microsoft
- Maturity
- Production
- Linked source
- nearcontact.com
Desire to increase operational efficiency and productivity
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 4
- 1End-to-end sales process automation with AI agents
- 2Predictive maintenance using IoT and Azure AI
- 3Cross-channel context-aware customer service automation
- Need for seamless automation across multiple business departments.
- Desire to increase operational efficiency and productivity.
- Pressure to improve customer service and field operations outcomes.
- Legacy systems couldn’t support the AI-first or predictive workflows required for growth.
- Implemented Microsoft Dynamics 365 for core business automation.
- Deployed Power Platform tools (Power Automate, Power Apps, Power BI) for low-code workflow automation and analytics.
- Leveraged Microsoft Dataverse for unified data and Copilot Studio for custom AI agent creation.
- Integrated Azure AI and IoT for predictive maintenance in field services.
- Up to 30% productivity gains overall.
- 20–25% improvement in first-time fix rates.
- 15% increase in customer service agent productivity.
- Reduction in manual effort and administrative burden via automation.
Architecture
The architecture unifies Dynamics 365, Power Platform, and Copilot Studio on Microsoft Dataverse, enabling seamless data flow and orchestration of AI agents. Power Automate triggers implementation workflows, while Power Apps and Power BI deliver analytics and real-time technician guidance, and Azure AI and IoT process predictive maintenance data, with multi-agent orchestration supporting end-to-end automation.
Sources & evidence1
Evidence: Medium50/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Quantified outcome available
- Technical implementation details available
Published: Nov 3, 2025Publisher: nearcontact.com
AI-generated summary. Verify important details with the linked sources before relying on this case.
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