CivilFlow.ai

A bias-corrected, basin-operational climate-and-hydrology knowledgebase assembled for reservoir decision support: a pre-loaded CMIP6 dataset of 13 General Circulation Models x 4 SSP scenarios (SSP126/245/370/585) at daily timestep and 0.25-degree resolution covering South Asia, bias-corrected by Empirical Quantile Mapping against IMD gridded observations, fused with continuously ingested satellite precipitation, evapotranspiration and temperature (ESA Sentinel, Copernicus, NASA MODIS/TRMM, SRTM), and bound to calibrated hydrological models and reservoir-balance simulations for a multi-purpose dam portfolio of 1,440+ large dams. The latent licensable asset is not the raw CMIP6 or IMD data (both open) but the bias-corrected, basin-aligned, demand-segmented, operations-ready derivative layer plus the calibrated model and operating-rule library per reservoir.

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Universe, instruments and categories.

Industry: Water UtilitiesElectric Utilities
Instruments: equitiescommodities
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Type: not stated
Format: Web-platform hosted gridded and tabular time series: pre-loaded model-ready climate cubes (daily, 0.25-degree, per GCM per SSP) plus per-reservoir time series and what-if scenario outputs, presented through role-based dashboards for basin staff, department staff and state officials, deployed on the client's own infrastructure rather than sold as a downloadable feed
Volume: est. 0.5-1 billion climate grid-cells in the hosted knowledgebase: 13 GCMs x 4 SSP scenarios x daily timestep x ~2,000-4,000 South Asia cells at 0.25-degree x ~100+ years per run = roughly 10-100M values per GCM-scenario pair; plus per-reservoir calibrated hydrology, storage and demand series across a portfolio designed to scale to 1,440+ large dams, currently deployed on a ~30,800 km2 sub-basin — so the operational layer is in the millions of records today and multiplies with each templated dam configured
Users: N/A in a commercial sense — deployment is project-based for government and institutional clients (a state water-resources department operating 1,440+ large dams, funded through a UN development programme with a prime engineering consultant). The firm's client base is counted in engineering engagements, and as a remote-first specialist consultancy that is plausibly in the low tens of concurrent programmes.
History: 50 years
Update frequency: not stated
Growth: Active — a published, current case-study portfolio spanning climate reservoir decision support, flood early warning, basin-scale DSS, climate-resilience platforms, GHG inventories and engineering-software plugins, delivered remote-first with a documented UN-funded programme and a named prime-consultant partner; growth is project-won rather than product-revenue-led
Launched: est. 2022-2025 for CivilFlow.ai's platformised offerings (the case study describes an upgrade of an earlier-stage CC-DSS already piloted at smaller reservoirs in the same state, so the reservoir-decision-support product line predates this engagement; the firm positions itself as a recent engineering-software specialist across flood early warning, basin decision support, GHG inventories and CAD plugins)
Delivery: not stated
Entity mapping: not stated
Sample: not stated
Point-in-time: not stated
Licence: not stated

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