NYB.AI Launches Vecura 2.0, an Agentic Platform for Molecular Discovery
NYB.AI, a Singapore-based AI startup, released Vecura 2.0 on June 1, 2026, a platform designed to connect molecular simulation tools, scientific databases, AI models, and GPU infrastructure into a single workflow. The upgrade moves beyond providing access to separate tools toward automating how those tools work together in drug discovery and life science research.
Most research teams today juggle fragmented systems. A pharmaceutical company might use one platform for compound analysis, another for toxicity assessment, and a third for data retrieval. This fragmentation slows adoption of frontier AI models and makes scaling difficult, especially for smaller biotech firms and ingredient innovators without dedicated computational infrastructure.
From tool access to autonomous workflows
Vecura 1.0 aggregated hundreds of AI models and scientific tools into connected workflows. Vecura 2.0 adds an agentic layer that reasons across the entire discovery process.
The new system understands research objectives, retrieves relevant scientific context, selects appropriate models, coordinates execution across tools, compares outputs, and generates structured recommendations for next steps. This shifts the platform from a tool repository into a system that assists scientists in making research decisions, without requiring them to manually coordinate between separate applications.
Scientists can focus on research direction rather than infrastructure management. The agentic approach also supports NYB.AI's stated goal of making advanced AI discovery tools accessible beyond large pharmaceutical organizations.
NVIDIA partnership accelerates development
NYB.AI is building Vecura 2.0 using NVIDIA technologies as a member of the NVIDIA Inception program for startups. The company received access to NVIDIA Hopper GPUs through the NVIDIA Innovation Lab, along with engineering support to advance the platform's ability to plan, execute, and coordinate complex research tasks.
Vecura runs on NVIDIA accelerated computing across agentic orchestration, scientific modeling, data retrieval, and production deployment.
Token-based access model
NYB.AI is introducing a token-based credit system for Vecura 2.0. Biopharma companies, ingredient manufacturers, and research teams can purchase credits to run compute-intensive tasks such as compound screening, bioactivity prediction, and molecular docking without building their own infrastructure.
Public demonstration planned
NYB.AI will showcase Vecura 2.0 at the NVIDIA Inception Startup Showcase during InnoVEX 2026 (June 2-5, 2026, in Taipei). The demonstration will cover applications across pharmaceuticals, nutraceuticals, cosmetics, food science, and consumer health.
Learn more about AI for Science & Research and how generative AI and large language models are being applied in discovery workflows.
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