Resize Small Medium Large Powered by the upgraded RSI engine, the platform unifies data, models, experiments and production to accelerate materials innovation
BEIJING, Oct. 26, 2026 /PRNewswire/ -- Fabarta (Beijing Fengqing Technology Co. , Ltd. ), a leading provider of enterprise-grade AI agents and knowledge engines, today announced a major strategic upgrade to its AI for Science (AI4S) platform: the official launch of Fabarta Science Intelligent-the platform's newly upgraded core engine, driven by RSI (Recursive Self-Improvement)-alongside the evolution of AI4S into AI4S&E (AI for Science & Engineering), which now covers the core chain of R&D and production. The upgrade marks a comprehensive enhancement of Fabarta's AI4S platform, equipping it with frontier capabilities including multi-agent collaboration, multiscale model self-evolution and physics-informed AI hybrid modeling. The platform now connects the entire chain-from literature review and formulation design to dry- and wet-lab experimental validation, digital pilot-scale scale-up and industrial mass production-moving toward continuous self-iteration and accelerating the shift of materials R&D from traditional trial-and-error empiricism to a new paradigm driven by AI and knowledge. Meanwhile, as an important milestone in advancing the company's global expansion and capital market presence, Fabarta has been invited to join the first batch of "Hong Kong Top Talent Ecosystem Partners. " Founder and CEO Andy Gao and Co-founder and COO Michelle Ge will lead a delegation to attend Asia's largest fintech event-Hong Kong FinTech Week × StartmeupHK 2026-on November 2, where they will receive official plaque at a dedicated session and showcase the breakthrough achievements of Fabarta's AI4S platform and enterprise-grade AI Agents to over 45,000 global industry leaders. From Single-Point Tools to Full-Chain Integration: The AI4S Platform Takes a Leap with RSI
As an AI leader deeply engaged in the fine chemicals and new materials sectors, Fabarta's earlier AI for Science platform had already demonstrated notable results in scenarios such as intensive literature reading, data management and single-point algorithm-based prediction. Yet in the "deep-water zone" of the materials industry-moving from the laboratory to the production line-conventional AI4S tools often remain at the level of "single-point computing" or "assisting with paper publication. "
To address this bottleneck, Fabarta systematically iterated on its AI4S platform, deeply embedding its self-developed RSI intelligent architecture into the platform foundation. Through its "Four Modules" and "Three Loops," the upgraded AI4S platform is now capable not only of literature Q&A and molecular generation, but also of adaptive model evolution, multiscale physical simulation and digital-twin calibration-accelerating the leap of Fabarta's AI4S platform into an "industry-grade, integrated R&D-production platform with self-iteration capability.