AI-Optimized Decarbonization: Carbon Capture & Hydrogen Intelligence

Solvra.AI, based at the LIT Open Innovation Center in Linz, develops cutting-edge AI control systems for decarbonized industrial energy — including solvent regeneration in CO₂ capture and AI-optimized hydrogen production in local renewable energy hubs.

AI-Optimized Solvent Regeneration (Solvra.AI Control Platform):

Using real-time sensor data from industrial plants and energy hubs, our platform applies Deep Reinforcement Learning to continuously optimize:

Solvent flow & regeneration energy in CO₂ capture
Electrolyzer operation & hydrogen output in smart energy hubs
Thermal & pressure management across integrated systems

-Retrofit-Ready & Vendor-Agnostic:

Our modular AI platform integrates seamlessly into CO₂ capture units and hydrogen production systems — supporting any solvent, electrolyzer, or plant setup. Ideal for sectors like cement, steel, chemicals, energy storage, and smart industrial districts.

- Future-Ready Architecture

Built for scalable deployment, cloud connectivity, and full compatibility with SCADA/DCS systems. Our modular design enables phased integration of both CO₂ capture and hydrogen production systems — from real-time monitoring to fully autonomous AI control.

AI Optimized Smart Energy Hub

-Making industrial CO₂ capture affordable and scalable with AI-optimized solutions.

Innovation for a Net-Zero Future

At SolvraAI, we harness the power of AI to transform industrial decarbonization — from cutting the high energy cost of solvent regeneration in CO₂ capture systems to optimizing hydrogen production in smart energy hubs. Our intelligent control platform enables scalable, retrofit-ready solutions that reduce emissions, boost efficiency, and support a net-zero future.

AI-Optimized Carbon Capture & Hydrogen Control

Using Deep Reinforcement Learning and real-time sensor data, our system optimizes CO₂ solvent regeneration and hydrogen production processes. This dual optimization cuts energy use by up to 30%, ensures >90% CO₂ capture efficiency, and boosts hydrogen yield — enabling cost-effective upgrades across hard-to-abate industries.

AI-Optimized Solvent & Hydrogen Regeneration

Cutting carbon and boosting efficiency in CO₂ capture and hydrogen production.

Solvra.AI focuses on the two most energy-intensive processes in decarbonization: solvent regeneration in CO₂ capture and hydrogen generation via electrolysis.

Using Deep Reinforcement Learning (DRL) and real-time plant data, our system:

Reads: Flue gas composition, pressure, solvent temperature, flow rates, electrolyzer metrics, and steam availability
Learns: In real time, adapting to plant conditions and operational shifts
Controls: Steam input, solvent circulation, electrolyzer setpoints, and energy routing
Delivers: Up to 30% energy savings in solvent regeneration and increased hydrogen yield in smart energy hubs

This dual-purpose, retrofit-ready AI module unlocks scalable upgrades for industrial decarbonization — from cement plants to hydrogen hubs.

Milestones

2025

MVP Completed – AI for Carbon Capture & Hydrogen Optimization

Solvra.AI is founded to tackle two of the most energy-intensive decarbonization challenges: solvent regeneration in CO₂ capture, and hydrogen production optimization.

✅ MVP completed for DRL-powered control platform

🧠 Trained on real industrial datasets (flue gas, steam, pressure, electrolyzer inputs, energy flows)

📍 Based at LIT Open Innovation Center, Linz

🚀 Ready for dual pilot testing with industrial partners (CO₂ capture & hydrogen energy hubs)