AI Data Inc. Introduces '7 Strategist Models' to AI FusionEnergy on IDX, an AI Platform Conquering the Next-Generation Energy Sector

AI Data Inc. (Headquarters: Minato-ku, Tokyo; CEO: Takahito Sasaki; hereafter 'AI Data'), a corporate data and AI utilization company, has announced the expansion of its 'AI FusionEnergy on IDX' AI platform for nuclear fusion and next-generation energy research, originally launched in December 2025, with the introduction of the new '7 Strategist AI Models.'

'AI FusionEnergy on IDX', built on the 'AI Komei on IDX' foundation, is an AI data platform that templates business knowledge, on-site expertise, and operational processes in the fusion and energy sectors. It stores these in the Knowledge Team Drive on IDX to provide them as ready-to-use AI solutions, supporting researchers' strategic thinking through interactive dialogue.

The newly introduced 7 Strategist Models are overall optimization AI models built on the 'National Strategist OS for Fusion Energy' concept. They integrate and structure fragmented research data and knowledge across seven domains: plasma, magnetic field control, materials, core design, simulation, R&D strategy, and intellectual property. By cross-supporting fusion startups, research institutions, universities, heavy machinery/electrical manufacturers, and policy organizations, the models aim to form a Japanese fusion industry ecosystem and dramatically improve international competitiveness.

■ AI FusionEnergy on IDX: AI Platform for Next-Generation Energy Research

https://www.idx.jp/aifactory/list/fusionenergy/

■ Background: Fusion is shifting from 'Research Competition' to 'Industrialization and IP Battles'

The Japanese government has selected 'next-generation energy' as one of its 17 priority areas, aiming to realize a decarbonized society and restore its status as a science and technology-oriented nation. Driven by international collaborations like the ITER project, domestic national projects, and rapid entry by startups, fusion energy is transitioning from a 'research' phase to an 'industrialization' phase.

However, Japan's fusion industry faces several structural challenges:

- Fragmentation of Data and Knowledge: Data is siloed across research institutions, universities, and private companies. Experimental logs, measurement data, and failure logs are not integrated, preventing improvement loops.

- Delayed Integrated Design due to Siloed Structures: Optimization occurs individually for materials, superconductivity, control AI, cooling, and shielding, making integrated design and connection to mass production models difficult.

- Opaque Industrialization Roadmap: Ambiguity around 'when', 'who', 'where', and 'how' mass production will happen hinders investment and supply chain growth.

- Lagging in Patent Competition: While the US and China are rapidly increasing fusion patents, Japan leads in research papers but lags in patenting, failing to translate technical advantages into revenue and negotiating power.

- Disrupted Technology Transfer: The expertise of veteran researchers remains tacit and is not passed on to younger generations, expanding the 'silent loss' that slows research speed.

The 7 Strategist Models of 'AI FusionEnergy on IDX' provide the following features and values to solve these challenges.

■ Features of AI FusionEnergy on IDX: The 7 Strategist Models

1. Plasma Strategist

Integrates and structures papers, experimental reports, and technical literature on plasma control on IDX. The AI provides knowledge support for formulating control strategies, considering predictive detection approaches, and achieving stabilization, accelerating researchers' decision-making.

2. Magnetic Field Control Strategist

Integrates technical information, patents, and research data regarding superconducting coil design and magnetic field configuration, supporting the consideration of control algorithm improvements and IP generation points.

3. Material Strategist

Integrates research data, papers, and patent information on irradiation, degradation, and high heat flux materials. The AI assists in organizing the rationale for material selection, formulating hypotheses for lifespan estimation, and considering material patent strategies.

4. Core Design Strategist

Integrates design information, simulation results, and technical literature related to vacuum vessels, divertors, and neutron shielding, supporting the formulation of design hypotheses and the consideration of improvement approaches.

5. Simulation and Experimental Strategy Strategist

Converts past experimental scenarios, success/failure conditions, and simulation models into knowledge. The AI proposes the next experimental approaches and research hypotheses to tackle, streamlining research trial and error.

6. R&D PMO Strategist

Integrates R&D themes, technology roadmaps, and international collaboration information. The AI assists in organizing processes, visualizing risks, and generating materials for decision-making, enhancing the 'speed and consistency' of long-term, large-scale fusion R&D across multiple organizations.

7. IP Strategist (Tokkyo.AI Collaboration)

Analyzes global fusion-related patents (plasma control, magnet design, materials, coil manufacturing, shielding, heat exchange) in collaboration with Tokkyo.AI. The AI supports the visualization of competitive strengths and weaknesses, white spaces, conversion of papers to patents, and consideration of workarounds, functioning as the 'shield and spear of IP' in fusion research.