SQUIDBOT.io is where engineers tinker & discover solutions
A non-predictive approach that attempts to find asymetries in complex process data. To simplify, our algorithms minimize the probabilities of mediocre output scenarios. A strategy that aims at building robust, survival-based agents, is what we believe it can be achieved with SQUIDBOT.io when mitigating production down-time or failure risk.
To learn more about how our platform works, please read our blog.
A sample of plant-scale solutions
Product quality: Particle Size Distribution (PSD) in coal and cement grinding
Burning efficiency improvement: High-temperature Kilns in Mineral, Mettalurgy & Aluminium industry
Product output: Distillation columns, steel & mineral industry, energy & utilities
Widescale cooling, heating & energy management
Survival-Based Agents: Risk is mitigated by definition during KPIs or emission improvement thanks to the our agent algorithm structure that is based on survival-functions that account for bad events probability
Long-term robustness against MTBF
Long-term advantage: Less probability for bad process states
Largescale minimization: NOx and SOx emission in power plants and steel industry, HFCs in Alumina production...
Energy use & WHR: Our agents can be trained to propose advanced strategies in energy minimization and WHR management systems.
Get more solutions out of our platform
Build anything with SQUIDBOT.io — customized solutions for any heavy industry business or large-scale energy management field can be brainstormed within hours between engineering teams, operators & maintenance personnel. SQUIDBOT.io is made for the intuitive decision-making of manufacturers, that is developped through years on the factory floor.
Learn more the process of building decision-making industrial agents.