SAJAG सजग
Smart Asset Judgement & Availability Guard
“Predict the failure. Protect the mission.”
THE PROBLEM
Indian Army vehicles break down because maintenance follows a calendar, not actual condition. Workshops wait weeks for spares that should have been pre-positioned. Fixed-interval servicing either over-maintains (wasting resources) or under-maintains (missing failures). When equipment fails unexpectedly, spares are often 2,000 km away in a depot - and the vehicle sits idle for weeks. SAJAG changes both: it predicts failures based on how each vehicle is actually used, and tells Ordnance exactly what spares to stock, where, and when.
THE SOLUTION
What SAJAG Does
SAJAG is an AI platform that predicts when military vehicles and equipment will fail, what spares will be needed, and when to stock them - turning reactive breakdown-repair into proactive predict-prevent. It works with data the Army already has: service records, breakdown logs, and deployment histories. No sensors required for Phase 1.
Every prediction is conditioned on terrain and climate. The same vehicle behaves fundamentally differently in Ladakh (-40°C, 5,500m altitude) vs Rajasthan (+52°C desert) vs Northeast monsoon zones. This terrain correlation is SAJAG's core intelligence - no commercial platform models this because no commercial fleet operates across this range. Classical ML algorithms (XGBoost, survival analysis, time-series forecasting) run on standard CPU hardware. No GPU. No LLM dependency. No internet required for any core function.
सजग (SAJAG) - Alert. Vigilant. Watchful. In Indian Army culture, "Sajag raho" (stay alert) is drilled into every soldier from basic training onwards. SAJAG stays alert to equipment degradation so your fleet stays mission-ready.
CAPABILITIES
Key Features
Vehicle Health Scoring
AI-generated 0-100 health score per vehicle and per system (engine, cooling, transmission, electrical, brakes, suspension). Updated after every data ingestion event with historical trend tracking.
Failure Prediction Engine
Survival analysis + classification hybrid predicts failure probability within 7/14/30/60/90 day windows per vehicle per system. Contributing factors and recommended actions included.
Terrain-Weather Correlator
Core differentiator. Adjusts all predictions based on deployment terrain - high altitude, desert, monsoon, plains. Terrain wear factors calibrated from real operational data.
Spares Demand Forecasting
30/60/90-day spares demand forecast per formation. Maps predicted maintenance to spares Bill of Materials. Dead stock identification and periodicity analysis.
Breakdown Pattern Mining
Association rule mining identifies co-occurring failure patterns. "When ALS operates at >4,000m for >90 days, fuel injection system failure follows electrical failure 89% of the time."
Mission Reliability Calculator
Single reliability percentage per vehicle and per formation. What-if scenarios: "If we service these 3 vehicles first, reliability goes from 64% to 86%."
Maintenance Alert Engine
CRITICAL (7 days) / WARNING (7-30 days) / ADVISORY (30-90 days) alerts with recommended actions, spares lists, and acknowledgement workflow.
Data-First Architecture
Works with existing paper records digitised via CSV/Excel upload, web forms, or mobile app. No sensors required. Sensor integration available for future-inducted vehicles.
DEPLOYMENT OPTIONS
Product Tiers
SAJAG OnPrem
Deployed on Army formation's existing server infrastructure. Works on local network with no internet. Data never leaves formation. Suitable for operational deployments and sensitive formations.
SAJAG Cloud
Full stack on NIC Cloud for rapid pilot deployment. All data on Indian government infrastructure. Suitable for initial evaluation and demonstration.
SAJAG Hybrid
Phase 2Formation-level instances for data collection and local predictions. Command-level aggregator for cross-formation visibility. Ordnance echelon accesses demand forecasts from command level.
WHY NOT A FOREIGN ALTERNATIVE?
Why SAJAG?
“Every day, military vehicles break down because we maintain them on a calendar instead of their actual condition. SAJAG predicts failures based on how each vehicle is actually used - in which terrain, at what altitude, in what temperature - and tells Ordnance exactly what spares to stock, where, and when.”
INTEGRATION
Works With
DESIGNED FOR
Who It Serves
Proudly Made in India
Engineered in India with world-class standards. Deployable anywhere in the world. Full source code available for sovereign audit. No vendor lock-in. No foreign dependencies.
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Learn MoreReady to See SAJAG in Action?
Working prototype available within 30 days. Schedule a live demo with our team tailored to your operational requirements. Anywhere in the world.