Tech Mahindra and Microsoft Launch Ontology-Driven Agentic AI Platform for Telecom and Data Mesh
Tech Mahindra and Microsoft unveiled an ontology-driven Agentic AI platform built on Microsoft Fabric and Azure AI Foundry to accelerate telecom and enterprise data modernization.
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What Happened
Tech Mahindra (NSE: TECHM) has collaborated with Microsoft to launch an ontology-driven Agentic AI platform designed to accelerate telecom and enterprise data modernization. Built on Microsoft Fabric and Azure AI Foundry, the solution enables explainable, auditable, and real-time AI-powered decision-making while supporting secure, governed deployment of AI agents. The platform addresses the growing gap between enterprise metadata and actionable insight as telecom operators expand through mergers and acquisitions and manage increasingly complex data ecosystems.
By transforming enterprise metadata into structured, reusable data products, the platform fast-tracks data mesh adoption from strategy to execution. Through multi-agent orchestration, it enables real-time monitoring, reasoning, and recommendations across key telecom use cases. Its semantic-first design helps reduce hallucination risk, improves root-cause analysis, and supports compliant AI operations in highly regulated environments.
- churn prediction
- fraud detection
- revenue assurance
- network optimization
“Telecom operators are moving beyond AI experimentation toward scalable intelligence that delivers measurable business outcomes. Our ontology-driven Agentic AI platform, developed with Microsoft, provides a governed semantic foundation for explainable insights, real-time decisioning, and cross-domain intelligence. This reinforces Tech Mahindra’s position as a strategic AI-led transformation partner”
The value proposition for telecom customers is to accelerate production-grade adoption of agentic AI solutions, enable faster go-to-market at scale, and optimize both development and operational costs. The collaboration strengthens Tech Mahindra’s partnership with Microsoft and advances joint go-to-market efforts. The unified architecture brings together governed data, semantic models, knowledge graphs, and task-specific AI agents into a scalable, enterprise-ready stack, modeling canonical telecom entities and business rules across customer, network, revenue, and operations domains.
“For telecoms, realizing value from scalable AI depends on intelligence and trust. Built on Work IQ, Fabric IQ, and Foundry IQ, Microsoft IQ connects AI, data, and business context, giving AI agents deep awareness of operations, decision-making, and customer interactions. Leveraging Microsoft IQ, Tech Mahindra automates data products through its Agentic AI–powered Data Product Manager and delivers ”
The collaboration aligns with Tech Mahindra’s ‘AI Delivered Right’ strategy, which advances enterprise AI adoption through scalable, ontology-driven solutions that enable organizations to transition from pilot initiatives to governed, production-grade AI transformation. For telecom providers, the solution delivers trusted, auditable artificial intelligence, unified operational visibility, and faster time-to-value. Enterprises advancing Data Mesh strategies benefit from accelerated data product creation, stronger utilization of governance investments, and privacy-compliant innovation.
Why this matters
For telecom operators, the platform turns scattered metadata into reusable data products, enabling explainable, real-time AI decisions and cutting hallucination risks. It helps them move from AI pilots to production-scale, governed deployments, with faster time-to-value and lower costs. Enterprises using data mesh also benefit from accelerated data product creation and privacy-compliant innovation.
Terms in This Story
- Agentic AI
- AI systems that can independently perform tasks, make decisions, and take actions to achieve goals, often using multiple agents.
- Ontology
- A formal representation of concepts and relationships within a domain, enabling shared understanding and structured data.
- Data mesh
- A decentralized data architecture that treats data as a product, with domain teams owning their data domains.
- Knowledge graph
- A structured network of entities and their relationships, used to integrate and reason about data from multiple sources.
Summarised from the linked release; details can be imperfect — always verify against the original source.