From grid operations and renewable forecasting to crop analytics, flood monitoring, and geospatial intelligence — Quenext transforms complex planetary data into precision decisions.
Spanning geospatial intelligence, energy forecasting, market optimization, data integration, and decision analytics — powered by proprietary AI and deep learning.
Search the earth the way you search the web — by context, not coordinates. Type a survey number, a village name, or a crop type and GlobeZoom returns a full 360° intelligence profile: parcel boundaries, crop history, soil moisture, vegetation health, flood risk, and ownership records. 500M+ parcels. Retail simplicity. Institutional depth.
AI-powered decision support system for energy utilities. Unified operations platform with real-time visibility into demand patterns, generation mix, and grid stability. Multi-revision forecasting with sub-2% MAPE accuracy. Integrated with satellite data, weather, and agri-load estimation. Go live within 2 weeks.
Institutional-grade market operations infrastructure for power procurement and merchant trading. Integrates spot and forward markets with portfolio-level position management, settlement reconciliation, and multi-market analytics across IEX, PXIL, and bilateral channels.
Aggregate and optimize distributed energy resources into dispatchable virtual power plants. Scalable from rooftop solar clusters to utility-scale battery networks with real-time optimization, market participation, wide area monitoring, and hazard alerts.
Talk to your energy analyst. ARIA is a voice-enabled conversational AI that serves as a virtual product manager and domain expert. Ask about demand forecasts, market prices, generation mix, weather impact, DSM penalties, renewable tolerance bands, or run what-if scenarios — all through natural voice in 10+ Indian languages.
Advanced energy optimization using stochastic optimization with CVaR and linear programming. Optimizes generator dispatch, market participation, and portfolio hedging across 96 daily trading blocks. Interactive risk-cost tradeoff efficient frontier explorer.
The backbone data layer powering all Quenext products. Manages data sources, connectors, and ingestion pipelines across the entire platform. Live integrations include IEX Market Data, Vidyut Pravah, IBM Weather Company, MERIT India, PXIL Exchange, and state SLDC feeds.
Unified analytics constellation connecting all platform products into a single intelligence layer. Cross-product data correlation, unified dashboards, and enterprise-grade reporting across energy, agriculture, and geospatial domains. Centralized monitoring with multi-tenant support and role-based access control.
Domain-specific engines extending the core product suite.
Physics-hybrid solar forecasting with irradiance models, panel conversion curves, satellite cloud tracking. Handles soiling, temperature derating, and inverter efficiency. MAPE ≤4.2%.
Hub-height wind power prediction using multi-level atmospheric modeling, turbine-specific power curves, and terrain-adjusted wake effects. Ramp event detection. MAPE ≤5.8%.
Precision agriculture analytics at parcel level. Crop classification across 30+ classes, seasonal change detection, risk factor identification. Automated cultivation change mapping. Accuracy >92%.
River basin monitoring and flood prediction. Satellite-derived water extent, DEM, rainfall forecasts, upstream gauge telemetry. Real-time inundation mapping. 72hr lead time, >88% accuracy.
Purpose-built solutions integrating satellite data, weather data, market data, agricultural field data, and network intelligence.
Composable AI pipeline architecture with autonomous self-learning agents, 10 master agents, 40+ sub-agents, and 5 production pipeline configurations.
Representation-learning with multiple abstraction levels. Mix of statistical, tree-based, neural networks, and physics-hybrid models with champion-challenger rotation. Automated hyperparameter optimization, SHAP-based feature importance, and probabilistic uncertainty bounds.
Seamlessly combines weather data (3×3 km grid), satellite/remote sensing, SCADA network data, agricultural field data, market feeds, and distributed asset maps. NWP ensemble predictions with 8 meteorological parameters. 200+ engineered features with 36-state calendar encoding.
Agents encapsulate roles with autonomy and policies (LLM + tools + memory). DAG-based orchestration with Kafka/Delta for data, Ray/Airflow for scheduling, MLFlow for lineage, Feast for features. REST/gRPC serving with batch + realtime. CERC/SERC/IEGC regulatory compliance built in.
Autonomous agents across data, forecasting, and optimization layers — each with specialized sub-agents.
Multi-source data connectivity with SCADA, weather APIs, exchange feeds, FTP telemetry. Schema validation, format normalization, quality tagging. <200ms latency, 15+ sources, 99.97% uptime.
Statistical anomaly detection preserving genuine grid events. Z-score, IQR, isolation forest methods with dynamic historical baselines. 97.2% precision, <1.8% false positives.
Gap interpolation with 6 imputation methods (linear, spline, seasonal decomposition, k-NN, physics-constrained, ensemble). Handles up to 72h gaps. 99.1% accuracy.
Feature engineering with 200+ features: lagged, rolling statistics, exponential smoothing, cross-signal correlations. 8 weather parameters, 36-state holiday flags, SHAP-based importance ranking.
Primary forecast generation: gradient boosting, neural networks, physics-hybrid, autoregressive. 15-minute granularity across 6 horizons with automated hyperparameter optimization.
Error learning and bias correction from sliding 7-day windows. Regime shift detection (factory openings, policy changes). 12-18% improvement, real-time adaptation.
Multi-model synthesis with dynamic weight optimization and stack generalization. P10/P50/P90 prediction intervals. 3-7 models combined with stability monitoring.
Optimal dispatch across generation assets. Merit order economic dispatch, ramp constraints, 16 intraday revisions. IEGC-compliant 96 block/day scheduling.
Automated bid optimization for DAM, RTM, GDAM, TAM. Ladder, Block, RTC, Profile Bid strategies. VaR calculation, execution routing to IEX/PXIL. ₹0.2-0.5/kWh alpha.
8-round walk-forward validation with MAPE, MAE, RMSE metrics. CERC deviation settlement, SERC compliance reporting. Automated certificates and dashboards.
Electricity consumption forecasting across all 36 states and UTs.
Physics-hybrid forecasting for 4,200+ turbines across 8 states.
Irradiance-to-power conversion with Perez transposition and soiling models.
DAM and RTM spot rate forecasting for trading decisions.
Distributed resource orchestration combining forecasting, dispatch, and trading.
Satellite imagery to crop classification. Multi-temporal analysis across Kharif, Rabi, and perennial seasons for 500M+ parcels.
Multi-spectral and high-resolution image classification for land use, boundary detection, and asset identification.
End-to-end satellite imagery processing — NDVI, soil moisture, surface temperature, water body mapping, and change detection.
Flood forecasting — river basin monitoring combining satellite water extent, DEM, rainfall forecasts, and upstream gauge telemetry.
Quenext AI-ML vs industry benchmarks — consistently outperforming across all metrics.
Serving state utilities, national grid operators, and major financial institutions across India and globally.
Uttarakhand Power Corporation Ltd. — Live deployment for 3+ years with significant financial gains.
System tested for all DISCOMs in Western Region — Maharashtra, MP, Chhattisgarh, Gujarat, Goa.
Energy Atlas deployment for demand forecasting, scheduling optimization, and grid management.
Rajasthan Urja Vikas Nigam Limited — Energy Atlas for forecasting and scheduling optimization.
Bihar State Electricity Board — Demand forecasting and energy management solutions.
Crop identification & survey number linkage for crop loans powered by GlobeZoom.
Dubai Future Accelerators — Innovation challenge partnership with Dubai Electricity & Water Authority.
The only startup in Asia invited to the innovation challenge to work with DEWA (Dubai Electricity & Water Authority).
Winner for technology solutions in the smart city space — energy utility category.
The only Indian startup to represent India in Gothenburg, Sweden (2018-19) on Digital Innovation.
The only Indian startup with a global patent in forecasting and energy management including trade optimization. US Patent No. 10468883.
Energy grids. Farmland at scale. Credit decisions. AI systems built for the sectors the world runs on — deployed across Indian utilities, half a billion mapped land parcels, and bank lending desks. Twenty years in. Still building.
Indian Statistical Institute alumnus. 20+ years of AI and machine learning in the real world — energy, agriculture, financial services, earth observation, four continents. Multiple patents. Not interested in problems that already have good answers, and not convinced any problem does yet.
Technology entrepreneur who co-founded Theta Enerlytics — drones in the field, thermal surveys from the air, grid intelligence on the platform. Physical infrastructure made legible to AI, end to end. His fingerprints are on DigiYatra's face recognition system — one of India's largest deployed AI systems. 25 years of venture-building. One throughline: AI that works on real infrastructure, at India's scale.
Ready to transform your energy management or explore geospatial intelligence? Let's talk.