Welcome to NIRNAY,
AI-Assisted Operations You Can Trust
Metro operations are complex, but with Nirnay, they become effortless.
Our AI-powered platform transforms raw train data into clear insights,
runs instant what-if simulations, and flags conflicts before they happen.
The result?
Safer schedules, optimized fleets, and zero guesswork.
With Nirnay, your team makes faster, smarter, and more reliable decisions.
Features
Train Data Unification - Dashboard
All operational data, unified in one intelligent dashboard. Nirnay consolidates fitness reports, maintenance due dates, crew assignments, job cards, and depot capacities into a single, real-time interface. This unified view eliminates manual cross-checking, giving planners a holistic snapshot of fleet health and readiness. With filters, live updates, and drill-down capabilities, decision-makers can respond quickly and keep operations running without bottlenecks.
Explainable AI
Every recommendation made by Nirnay is transparent and explainable. Instead of a black-box AI, our system highlights why a train was selected for induction or why a depot was flagged as overloaded. Whether it’s an overdue maintenance task, capacity conflict, or operational mismatch, Nirnay provides clear justifications and actionable alerts. This builds trust in AI-driven decisions and ensures planners can defend and validate every scheduling choice.
What-if Simulations
With Nirnay, operational planners can experiment safely before committing. Our AI engine lets you simulate alternative induction schedules by adjusting variables such as depot capacity, train readiness, maintenance slots, or induction timings. Each simulation generates a comprehensive impact analysis—covering fleet availability, depot load balance, stabling requirements, and operational efficiency. This ensures every plan is evaluated from multiple angles, minimizing risks and enabling evidence-backed decisions.
Route Optimization
Induction planning isn’t just about timing — it’s about aligning the right train with the right depot at the right time. Nirnay continuously analyzes depot constraints, maintenance backlogs, and operational dependencies to suggest optimized allocation of trains across depots and routes. By reducing unnecessary shunting, balancing workloads, and ensuring compliance with operational constraints, the platform delivers a streamlined induction process that’s resource-efficient and conflict-free.