AI-powered electricity demand and renewable generation forecasting. A proposed B2B software platform helping energy teams anticipate consumption, forecast renewable output, and plan procurement with greater precision.
Industrial energy consumers and renewable portfolio operators face volatile markets where inaccurate demand expectations and unpredictable supply curves trigger severe financial exposure.
Manufacturing facilities face punitive peak-period surcharges when unexpected factory ramp-ups diverge from scheduled day-ahead bids.
Solar and wind farms are hostage to micro-climate fluctuations. Inaccurate scheduling triggers curtailment directives and PPA non-compliance.
A software platform purpose-built for energy procurement leaders, unifying multi-factor machine learning with domain-specific grid physics.
Ingests historical smart-meter telemetry, plant shift schedules, and ambient thermodynamic vectors to project consumption curves with sub-hourly accuracy.
High-resolution predictive modeling for solar PV and wind clusters. Incorporates multi-horizon numerical weather predictions across 15-minute timeblocks.
Equips energy portfolio managers to schedule open-access procurement, optimize bilateral PPAs, and orchestrate behind-the-meter BESS dispatch.
We partner with forward-thinking industrial energy consumers and renewable portfolio operators to benchmark AI predictions against historical operational data.
High-tension industrial consumers with connected loads exceeding 1 MW seeking to insulate operational margins against spot volatility.
Benchmark AI prediction accuracy against 90-day billing cycles to demonstrate quantifiable demand charge savings.
Utility-scale asset managers, solar developers, and wind operators governed by strict state and central grid scheduling codes.
Run historical generation logs through Sproflow's models to observe reduction in scheduling error margins and penalty exposure.
Provide 30–90 days of anonymized 15-min metering data. Zero software installation required.
Receive a comprehensive audit comparing baseline estimates against Sproflow AI predictions.
Deploy parallel predictions alongside existing operations to validate real-world tariff savings.
Sproflow Technologies Private Limited is an active corporation registered under the Companies Act, 2013, regulated by the Ministry of Corporate Affairs.
RL-4 Bajaj Nagar MIDC, Waluj at Aurangabad,
Aurangabad, Maharashtra, 431001 — India.
Connect with the founding team to initiate an evaluation of your facility's historical load profile, or apply for our supervised pilot deployment.
We review candidate facilities based on data availability (15-min or hourly telemetry) and tariff penalty exposure. All data is processed under strict bilateral NDA.
Company registration is actively verified with MCA (CIN: U20299MH2024PTC436766). Dedicated corporate email and telecommunications are currently being finalized.
Submit your facility details to schedule an initial historical telemetry evaluation.
No billing commitment · Historical data audit · Direct founding team access
Your facility parameters have been staged for the founding technical team. We'll reach out via bilateral channels.