186 real, deployable AI use cases across 14 industries and 3 technology layers — IoT, Augmented Reality and Multimodal AI. Filter by your domain and technology to discover exactly where AI creates value in your business.
Technology-specific, non-generic, real-world deployable. Each use case is a starting point for a scoped AI pilot or agentic workflow.
These are real, deployable agentic patterns that organisations are implementing today — not speculative experiments, but grounded workflow improvements across six functional areas.
NirmanAgents.ai designs AI systems that connect sensors, machines, wearables and augmented reality to create real-time, context-aware intelligence across operations and field environments.
Connect physical assets — machines, vehicles, fields, buildings — to AI systems that monitor, predict and act in real time without waiting for human intervention.
Overlay AI-generated guidance, diagnostics and contextual data onto the real world — empowering field workers, technicians and operators with hands-free intelligence exactly when they need it.
Combine vision, voice, text and structured data into unified AI systems that reason across all inputs — enabling richer diagnosis, more accurate decisions and faster automation.
NirmanAgents.ai helps you choose the right orchestration and tooling combination instead of forcing a single-stack approach. We advise on and implement across all major frameworks.
Graph-based orchestration for stateful workflows with explicit transitions, full control and debugging visibility. Best for complex, branching enterprise processes.
Role-based multi-agent collaboration for task flows that map naturally to functional teams. Ideal for workflows with distinct specialist roles.
Conversational agent networks and debate patterns suited to exploratory problem solving and iterative research workflows.
Lightweight orchestration with structured handoffs and strong model capabilities. Well-suited for production deployments with clear task boundaries.
Model Context Protocol (MCP) is emerging as the connective tissue between AI systems and business tools — CRMs, data warehouses, analytics platforms and internal apps — enabling agents to act on real context rather than answering in isolation. We architect MCP-native systems from day one.
Our AI Discovery Sprint takes 2–3 weeks and maps your business to specific AI opportunities, prioritises by ROI and produces a funded pilot roadmap.
2–3 weeks: IoT + AI + AR opportunity map & 12-month pilot roadmap with business case.
Full-stack pilot design: sensor + vision + voice + agentic system, end-to-end.
AR overlay + AI diagnosis for field teams, factories, hospitals or construction sites.
IVR modernisation or new voice-first AI agent for any-language operations.