Sakana AI and Mitsubishi UFJ Bank jointly developed an AI lending expert system that uses AI agents to support the loan workflow by automating information gathering, structuring, and analysis while keeping human decision-makers in control. The system received approximately 1,500 pieces of feedback during evaluation and achieved significant quality improvements by using AI to classify issues and optimize prompts iteratively. The collaboration demonstrates how AI can enhance professional work by automating routine analysis, freeing employees to focus on client relationships and qualitative judgment that cannot be quantified.
Sakana AI partnered with The Yomiuri Shimbun to analyze Chinese state-sponsored social media campaigns criticizing Japan using proprietary AI technology that extracts narratives and generates hypotheses. The system analyzed 1.1 million social media posts and identified multiple hypotheses, including one verified by the newspaper about coordinated timing of criticism campaigns. Sakana AI is now positioning defense and intelligence as a core focus area alongside finance for implementing AI in national security applications.
Sakana AI developed the Namazu model series by applying post-training techniques to open-weight foundation models to adapt them for Japanese cultural context and safety requirements. The Namazu-DeepSeek-V3.1-Terminus model maintained base model performance on benchmarks like MMLU-Redux and LiveCodeBench while improving neutrality and factual accuracy on politically sensitive topics from 28% to nearly 100% in answering related questions. Sakana launched Sakana Chat, a search-integrated service using Namazu models, following 1,000 beta testers' feedback to make localized AI models broadly accessible to Japanese users.
Sakana AI announced Sakana Marlin, its first commercial product, an AI research assistant for businesses that uses proprietary agent technology to conduct autonomous research. The system can complete complex business research over approximately 8 hours by itself, producing structured summary slides and multi-page comprehensive reports without human intervention after the initial prompt. The product integrates two core technologies—AB-MCTS for strategic exploration and AI Scientist frameworks for workflow automation—to enable efficient reasoning scaling that improves output quality with extended computational thinking.
Sakana AI completed development of a system for the Japanese government's Ministry of Internal Affairs and Communications to detect and counter disinformation on social media, using AI to visualize narratives, identify false information, and propose countermeasures. The system was demonstrated at a government event on March 16, 2026, combining multiple detection methods and providing transparency in AI decision-making processes. The technology aims to help Japan build domestic capabilities in AI-powered intelligence operations related to information security.
Sakana AI released Digital Ecosystems, a browser-based platform where small neural networks compete on a 2D grid, learning via gradient descent while the simulation runs. The system contains 40+ tunable parameters and runs entirely in the browser without installation. The research found that gradient descent stabilizes the ecosystem by preventing species from overextending or stagnating, enabling exploration of complex emergent behaviors.
Sakana AI launched Sakana Fugu, a multi-agent orchestration system that coordinates multiple foundation models to improve performance on coding, mathematics, and scientific reasoning tasks. The system is available as an API in two variants—Fugu Mini optimized for latency and Fugu Ultra for maximum performance—with OpenAI-compatible endpoints and based on ICLR 2026 research papers. Users can now integrate Fugu into existing workflows to automatically coordinate model collaboration without managing multiple API keys or manually selecting models for each task.
Sakana AI trained a 7-billion-parameter Conductor model using reinforcement learning to manage and coordinate a team of other AI models by writing natural language instructions tailored to each task. The Conductor achieved 83.9% on LiveCodeBench and 87.5% on GPQA-Diamond, surpassing individual models in its pool while dynamically adapting its approach—using single queries for simple questions and constructing multi-step workflows for complex problems. This approach enables AI systems to leverage collective intelligence by learning to delegate tasks across diverse models rather than relying on fixed human-designed workflows.
Sakana AI developed an automated proposal generation application for Sumitomo Mitsui Banking Corporation to streamline wholesale banking processes. The application reduces proposal writing time from one to two weeks to several hours or tens of minutes by deploying multiple AI agents that perform data collection, analysis, hypothesis building, and fact-checking. Bank employees can now focus on strategic problem-solving while AI handles document creation and identifies insights humans might overlook.
Sakana AI launched an Applied Team in early 2025 to implement generative AI technology in sectors like finance and defense. The company is developing command-and-control systems for defense that integrate large volumes of field data from drones and other sources to support rapid situational assessment and decision-making by military personnel. Software engineers at Sakana AI work on mission-critical defense applications using Python, TypeScript/Next.js, and Kotlin, with generative AI serving as an essential tool across implementation, goal-setting, and problem extraction.
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