AquaFlowz
NEW DELHI, India – October 20, 2025:
For decades, designing a water or wastewater treatment plant has meant long nights with spreadsheets, stitched-together models, and educated guesswork. Engineers juggle pilot data, cost assumptions, and energy estimates in separate files, re-running calculations every time a parameter changes and hoping it all lines up before the next review meeting. This is the world AquaFlowz was built to change.
AquaFlowz, developed by Cloudastra Technologies in collaboration with Prof. Anshul Yadav from the Department of Water Resources Development & Management, IIT Roorkee, is an AI-powered techno-economic assessment platform for water treatment. It brings advanced process simulation, cost modeling, and AI-driven parameter optimisation into a single environment so plant estimation work that once took weeks can now be done in hours, with far greater clarity and confidence.
“Most water treatment projects still rely on fragmented tools and manual iteration,” said Shivam Kushwaha, Founder & CEO, Cloudastra Technologies. “With AquaFlowz, we wanted to give engineers a co-pilot that understands process science, economics, and constraints, and helps them explore better designs much faster.”
The Challenge: Designing Critical Infrastructure with Incomplete Tools
Behind many treatment plants, there’s a familiar story. A city is growing, complaints about water quality are increasing, and regulators are tightening discharge norms. The municipal utility hires consultants to upgrade the plant. The team pulls together lab data, pilot results, vendor quotes, and rough cost curves and then models one configuration after another, manually adjusting pressures, recoveries, sludge ages, and contact times.
Every “what if” question raising recovery, adding a polishing step, changing energy assumptions – means hours or days of rework. Because tools are scattered, it is hard to see which option is most cost-effective over the life of the plant or whether the design is being overbuilt just to feel “safe.” This slows projects, increases reliance on conservative assumptions, and can lock communities into suboptimal infrastructure for decades.
What AquaFlowz Does Differently
At its core, AquaFlowz is a water treatment techno-economic assessment platform that brings process simulation, cost modelling, and energy analysis into a single, web-based environment. Instead of relying on disjointed tools, users can configure treatment trains, simulate performance, and understand cost and energy implications in one place.
The platform includes pre-configured flowsheets that span the full water-treatment chain from reverse osmosis with energy recovery and osmotically assisted RO to biological treatment based on the BSM2 framework, granular activated carbon systems, mechanical vapor compression, electrodialysis, nanofiltration, microfiltration, UV disinfection, prefiltration, and flexible multi-stage treatment trains. Each flowsheet comes with realistic operating ranges and typical optimum zones for critical variables such as pressure, recovery rate, sludge age, membrane area, bed depth, contact time, and flux.
Rather than asking engineers to build everything from scratch, AquaFlowz offers validated starting points that can be adapted to local conditions and project objectives.
AI as a Design Co-Pilot
What makes AquaFlowz truly game-changing is how it weaves AI into the design process.
Users can describe their problem in plain language such as a 10 MLD municipal wastewater plant with reuse ambitions, tight energy constraints, or a specific focus on organic removal and AquaFlowz responds with concrete flowsheet suggestions. It might propose, for example, a biological treatment train followed by GAC and UV disinfection, or a desalination-focused train with appropriate pre- and post-treatment.
An AI-powered parameter suggestion engine then offers starting values for key operating conditions. It suggests suitable pressure and recovery ranges for RO, sludge age and dissolved oxygen levels for biological treatment, bed depth and contact time for GAC, or flux and operating pressure for microfiltration. These suggestions are anchored in process science and engineering models developed with academic input, not just heuristic shortcuts.
“Our goal was to ensure that when AI speaks inside AquaFlowz, it speaks the language of real water treatment engineering,” said Prof. Anshul Yadav, Department of Water Resources Development & Management, IIT Roorkee. “We focused on embedding robust, research-backed models so that recommendations have technical depth behind them, while still being fast and intuitive for users.”
From Spreadsheet Chaos to Simulation-Driven Clarity
In one of its early applications, a municipal utility facing ageing infrastructure and new water-reuse targets used AquaFlowz to explore upgrade pathways. The team needed to compare conventional upgrades, RO-based reuse, and hybrid schemes under different influent qualities, energy prices, and demand scenarios.
Previously, such an exercise would have taken months of manual calculations and fragmented files. With AquaFlowz, the utility’s engineers configured multiple treatment trains within the platform, adjusted parameters in real time, and saw how changes affected water quality, recovery, energy consumption, and cost over a 20- 30 year lifecycle.
Instead of debating over disconnected spreadsheets, stakeholders reviewed a single set of simulations, cost curves, and process diagrams and quickly shortlisted a robust upgrade path with clear trade-offs between capital and operating costs. This shift from scattered calculations to simulation-driven collaboration is at the heart of what AquaFlowz promises.
Built for India’s Water Challenges, Ready for Global Use
While AquaFlowz is globally relevant, its early roadmap is closely aligned with India’s water challenges: growing cities, industrial corridors under pressure to reduce discharge, and public agencies pushing toward reuse and better resource management with constrained budgets.
By making robust design and techno-economic analysis faster and more accessible, AquaFlowz aims to support municipal bodies, industrial operators, consultants, and researchers as they navigate these pressures. Cloudastra plans to extend the platform with more region-specific cost data, additional flowsheets, and integrations with asset management, GIS, and compliance tools over time.
About AquaFlowz
AquaFlowz is an AI-powered water treatment techno-economic assessment platform developed by Cloudastra Technologies in collaboration with Prof. Anshul Yadav, Department of Water Resources Development & Management, IIT Roorkee. AquaFlowz enables municipalities, industries, consultants, and researchers to design and optimise water and wastewater treatment systems through advanced process simulation, AI-driven parameter optimisation, lifecycle cost analysis, and intuitive, web-based interfaces.
By combining rigorous engineering models with intelligent assistance, AquaFlowz helps transform plant estimation from a slow, fragmented exercise into a fast, transparent, and data-driven decision process.
About Cloudastra Technologies
Cloudastra Technologies is a Noida-based digital engineering and cloud consulting company specialising in AI, DevOps, Cloud Engineering, Cybersecurity, and Digital Product Development. Working with clients across India, the US, the UK, and the UAE, Cloudastra helps organisations design, build, and scale secure, high-performance digital platforms.
Guided by its philosophy “Discover | Build | Grow”, Cloudastra partners with domain experts and institutions to build products like AquaFlowz that solve complex, real-world problems in a practical, scalable way.
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📧 contact@cloudastra.co
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