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Combines machine learning, mathematical optimisation and automated workflow definition on an API Saas platform, allowing business to rapidly develop and deploy advanced solutions.
About
SOLVER-AI is an AI-driven optimisation platform that combines machine learning, mathematical optimisation, and automated workflows to help businesses rapidly develop, deploy, and adapt advanced solutions for improved efficiency and smarter decision-making.
Our company was started 3.5 years ago by Dr Paolo Fantini, an aeronautical engineer who decided to leverage his years of experience within the optimisation field, creating an easy to use, cost-effective and easily-integrateable system.
Our target audience is B2B, including within the under-served SME or Mid Market space.
Key Benefits
Enhanced Efficiency: Provides businesses with real-time optimisation and actionable insights, enabling significant efficiencies in key processes.
Dynamic Adaptability: Continuously learns and adjusts to changing conditions, ensuring optimal performance in dynamic environments.
No Infrastructure Setup: Unlike Gurobi, Pyomo, or OR-Tools, users don’t have to set up environments.
Ease of Use: Pre-built, ready-to-use optimization models (like supply chain, logistics, route planning, etc.).
Cloud-Native Scalability: Fully hosted on AWS with autoscaling and load balancing.
Data Security: Data security, encryption, and compliance are baked into the system.
Enterprise-Grade Features: Ideal for businesses that want no-code or low-code optimization.
Applications
While SOLVER-AI's optimisation platform is theoretically sector-agnostic, early adopters are emerging from two main areas - property management (e.g. consultancies, landlords, BMS providers) and "controlled farming".
In both arenas, limited data is required to train our models, and re-training depends on speed at which the respective environments change (i.e. with personnel use, retro-fitting, environmental change, etc.). Data typically provided by a range of sources (IoT, open source, etc.).
Property management: Energy savings, cost savings, environmental benefits
Controlled farming: Optimising water consumption, energy utilisation, crop yields.