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NYB.AI Launches Vecura 2.0, Bringing Agentic AI Workflows to Molecular Discovery, with NVIDIA

Money Compass by Money Compass
June 2, 2026
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NYB.AI Launches Vecura 2.0, Bringing Agentic AI Workflows to Molecular Discovery, with NVIDIA
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TAIPEI, June 2, 2026 /PRNewswire/ — Life science research is entering an AI era, but most discovery teams still cannot use frontier models at scale. Advanced AI models, molecular simulation tools, scientific databases, inference optimization and GPU infrastructure remain fragmented across separate systems. For many pharmaceutical companies, ingredient innovators, biotech teams, and research groups, this makes AI adoption slow, costly, and technically demanding.

Agentic AI for scientific execution. Vecura 2.0 moves beyond simple prompts and responses into autonomous scientific coordination.
Agentic AI for scientific execution. Vecura 2.0 moves beyond simple prompts and responses into autonomous scientific coordination.

NYB.AI, a Singapore Artificial Intelligence (AI) technology startup developing infrastructure for molecular discovery and life science research, aims to address this gap with Vecura, its agentic AI platform that connects scientific models, biological data, molecular analysis tools, and GPU accelerated computing into a unified discovery workflow.

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Vecura 2.0 builds on the original Vecura 1.0 platform, which provided access to AI models and scientific tools for molecular discovery. With the new agentic layer, Vecura 2.0 moves beyond tool access toward workflow execution. It is designed to help research teams define scientific objectives, retrieve relevant context, activate suitable models, compare outputs, and generate structured decision support with less manual coordination.

From model access to agentic workflows

Vecura was built around a simple premise: the next barrier in AI for science is not access to more models. It is the ability to make those models work together in discovery settings. The original Vecura platform brought hundreds of AI models, scientific tools, biological data, and molecular analysis capabilities into connected workflows, helping research teams move across compound analysis, target exploration, formulation research, toxicity assessment, and translational R&D without relying on separate systems at every step.

Vecura 2.0 extends this foundation with an agentic AI layer. The upgraded platform is designed to reason across the workflow by understanding research objectives, retrieving relevant scientific context, selecting suitable models, coordinating execution, comparing outputs, and generating structured next step recommendations. This evolves Vecura from a workflow platform into a more intelligent discovery system that can assist scientists at scale, closer to how real research decisions are made.

This agentic approach allows scientists to focus on research direction rather than infrastructure management. It also supports NYB.AI’s broader vision to democratize molecular discovery by making advanced AI models, scientific tools, and GPU intensive workflows more accessible to teams beyond large pharmaceutical organizations and specialized computational labs.

Scaling access through NVIDIA technologies

NYB.AI is strengthening Vecura’s agentic architecture for scientific discovery using NVIDIA technologies. As a member of the NVIDIA Inception program for startups, NYB.AI received access to NVIDIA Hopper GPUs through NVIDIA Innovation Lab, along with engineering guidance to advance Vecura’s ability to plan, execute, and coordinate complex research tasks. This support enables Vecura to move beyond isolated model execution toward connected workflows where scientific context, model selection, inference, comparison, and decision support operate as one system.

Vecura is powered by NVIDIA technologies spanning agentic orchestration, scientific modeling, data and retrieval, and production deployment – all running on NVIDIA accelerated computing.

NYB.AI is also developing a token based access model for Vecura 2.0. Through platform credits, biopharma companies, ingredient companies, and research teams can access AI powered discovery workflows such as compound screening, bioactivity prediction, and molecular docking. This model allows users to run compute intensive scientific tasks through NYB.AI’s platform without needing to build or operate their own infrastructure.

What’s next?

NYB.AI is bringing Vecura 2.0 to the NVIDIA Inception Startup Showcase at the Inception Pavilion during InnoVEX 2026 (June 2–5, 2026, Taipei Nangang Exhibition Center). The showcase will give NYB.AI an opportunity to validate Vecura 2.0 with enterprise leaders, investors, ecosystem partners, and international buyers, and strengthens its visibility within NVIDIA Inception ecosystem — demonstrating how agentic AI can move beyond model experimentation into usable research infrastructure for molecular discovery teams.

At InnoVEX 2026, NYB.AI will demonstrate how Vecura 2.0 can support molecular discovery and life science research across pharmaceuticals, nutraceuticals, cosmetics, food science, functional ingredients, and consumer health. The platform reflects NYB.AI’s broader mission to make advanced AI discovery infrastructure more usable, scalable, and accessible across the life science ecosystem.

About NYB.AI

NYB.AI is an AI biotechnology company developing infrastructure for molecular discovery and life science research. Its flagship platform, Vecura, is an agentic AI platform that connects AI models, scientific tools, biological data, retrieval systems, accelerated computing, and autonomous workflows to help life science teams shorten discovery cycles and prioritize high-potential candidates.

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