Who We Are

Axolotis.ai is a technology company pioneering the digital transformation of energy generation plans. We combine advanced optimization, real-time data, and agentic and generative AI to unlock untapped energy potential in existing energy producing- assets—maximizing efficiency, compliance, and sustainability.

Our Mission

To ensure every drop of energy fuel is used as efficiently as possible—turning power plants into a smart, flexible, and data-driven cornerstone of the global clean energy transition, with human expertise guiding every critical decision.

The Challenge

We aim to achieve human-in-the-loop automation through agentic AI—empowering operators with intelligent systems that augment decision-making while keeping humans firmly in control. Our technology serves as a trusted partner that handles complexity, surfaces insights, and executes optimized strategies, all under human oversight and guidance.

Global electricity demand—driven by AI and data centers—is expected to more than double by 2030. Hydropower remains under-optimized, limiting its contribution to a sustainable energy future. Electricity demand is rising faster than new generation can be built.

Optimization Engine

Our Vision

Our Solution

Unlock more power from existing assets through higher efficiency, reliability, and sustainability.

We offer a proprietary optimization and agentic AI framework that delivers human-in-the-loop automation:

  • Maximizes energy produced per unit of fuel (i.e. water in hydropower)

  • Reduces inefficiencies such as spillage and under-generation

  • Enhances operational compliance and environmental stewardship

  • Integrates seamlessly with storage and market operations for dispatch flexibility

  • Empowers operators with AI-driven insights while maintaining human oversight of critical decisions

Technology

Our technology integrates advanced optimization and active learning with agentic and generative AI to achieve supervised autonomy. This combination creates a seamless operator experience—where AI handles routine complexity, surfaces actionable insights, and executes optimized strategies, while humans retain oversight and control over critical decisions. The result is a more effective and efficient workflow that amplifies human expertise rather than replacing it.

Our optimization engine computes high-fidelity generation schedules that maximize system efficiency while honoring real-world constraints. It models complex turbine interactions, nonlinear hydraulic relationships, and operational limitations to deliver actionable, dispatch-ready guidance that improves reliability, compliance, and energy output.

Active Learning (Digital Twin Calibration)

Our Active Learning component fuses data and models, continuously updating the physics-based digital twin that powers our optimization framework. Using online inference and targeted experimental design, it identifies which system parameters—such as turbine efficiency curves, hydraulic losses, or head–flow relationships—require recalibration.

The streamlined adaptive loop:

1.     Detect when model accuracy drops below threshold

2.     Issue targeted test schedules to improve parameter estimation

3.     Measure real operating responses

4.     Update digital twin parameters and assess predictive reliability

When accuracy targets are achieved, updated parameters are transferred directly into the Optimization Engine to maintain high-fidelity predictions and robust operational decisions.

Potential Impact

  • Double digit efficiency gains demonstrated at a 200 MW existing hydropower system. With 1,283,000 MW of conventional hydropower and 189,000 MW of pumped storage globally, the market for optimization is immense.

  • Measurable OPEX/CAPEX savings through optimized operations and reduced maintenance needs

  • Transformation of legacy hydro assets into agile, intelligent systems where agentic AI and human expertise work in concert