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75F is a building automation technology company that designs, manufactures, and operates an Internet of Things (IoT) based Building Management…

AgBoost Tech Consultancy (ATC) is an India-based geospatial and artificial intelligence technology firm that builds decision-support systems for the agriculture, power utility, and infrastructure sectors. The company integrates satellite imagery, IoT sensor networks, spatial analytics, and predictive modeling to convert field-level data into operational decision tools.
ATC’s work spans three connected service lines: smart grid and utility infrastructure digitization, precision agriculture and climate resilience, and green energy and carbon credit ecosystems. In the utility domain, the company integrates geographic information system (GIS) data with enterprise platforms such as SAP, outage management systems (OMS), and SCADA to support asset mapping and digital twin modeling for power distribution networks. In agriculture, it deploys IoT weather stations, soil probes, and satellite-based crop monitoring to support irrigation optimization and yield forecasting.
The company was founded by Anand Prakash Arya, who has more than two decades of prior experience in GIS and utility digital transformation roles at organizations including Torrent Power, Noida Power Company, and Rolta India. AgBoost is headquartered in Greater Noida, Uttar Pradesh, and operates as an incubated startup supported by the AIC-GBU Incubation Centre at Gautam Buddha University. Its documented project work includes precision agriculture deployments in Madhya Pradesh and Bihar, and technical advisory support for bio-energy feedstock plantations.
AgBoost’s precision agriculture systems directly support SDG 2 by using satellite and IoT data to improve crop yield forecasting and resource use in farming operations. Its soil moisture and irrigation optimization tools contribute to SDG 6 by reducing inefficient water use in agriculture. Through its AgriPV and bio-energy feedstock advisory work, the company supports SDG 7 by helping integrate renewable energy generation with land use. Its integration of GIS with enterprise utility systems such as SCADA and OMS advances SDG 9 by modernizing power distribution infrastructure. The company’s core function, replacing manual or intuition-based resource decisions with data-driven monitoring across water, energy, and land, aligns with SDG 12’s resource efficiency goals. Its carbon credit verification services using satellite-based remote sensing directly support SDG 13 by enabling measurable tracking of carbon sequestration projects.
AgBoost’s delivery model centers on combining geospatial intelligence with field-level IoT deployment and enterprise system integration. For utility clients, the company maps physical grid assets using GIS and remote sensing, then integrates this spatial data with enterprise operational systems such as SAP, OMS, and SCADA to create digital replicas of infrastructure for predictive maintenance and asset lifecycle planning.
In agriculture, the methodology combines physical IoT hardware, weather stations, soil probes, and field cameras, with satellite and drone imagery processed through AI and machine learning models. Multispectral imagery is used to detect early signs of crop stress, disease, or nutrient deficiency before visible symptoms appear, while soil moisture data informs irrigation automation.
For carbon and green energy projects, the company applies high-resolution satellite imagery and remote sensing to measure and track carbon sequestration for verification purposes, and provides technical advisory for dual-use agrivoltaic (AgriPV) systems that combine solar energy generation with continued farming activity. Project delivery is documented through case studies covering specific deployments, including a precision agriculture implementation with ICARDA in Madhya Pradesh, a technical advisory engagement with Avalon BioEnergy for Moringa-based fuel feedstock, and a crop and soil health project with the NGO Apna Khet in Bihar. This project-based delivery model relies on field validation rather than purely remote or theoretical analysis.
AgBoost Tech Consultancy’s documented operations are concentrated in India, with projects delivered in Uttar Pradesh, Madhya Pradesh, and Bihar. The company has engaged with international partners on specific initiatives, including a precision agriculture project with ICARDA (International Center for Agricultural Research in the Dry Areas), reflecting some cross-border collaboration alongside its primary domestic operating base.
AgBoost Tech Consultancy represents a category of early-stage technology consultancy built on the transferable application of geospatial and enterprise IT expertise across otherwise distinct sectors: agriculture, power utilities, and green energy. Its founder’s prior background in utility GIS and grid modernization at established power companies gives the venture a degree of domain credibility uncommon among newer agritech startups.
The company’s documented project work, spanning precision agriculture in partnership with an international agricultural research body, bio-energy feedstock advisory, and soil health improvement projects, indicates practical field deployment rather than purely conceptual offerings. Its combination of IoT hardware, satellite-based crop and infrastructure monitoring, and enterprise system integration addresses a genuine gap for organizations seeking to modernize resource management without building in-house geospatial capability.
As an early-stage, incubator-supported startup, AgBoost’s scale of operations and long-term financial sustainability are not independently documented beyond its startup registry status. Its sustainability contribution is most clearly evidenced in resource efficiency and climate resilience applications for agriculture and infrastructure, though publicly available information on quantified impact, such as measured water savings or emissions reductions, is limited. Procurement teams evaluating AgBoost should weigh its specialized domain expertise against its early-stage scale.
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