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BioMetis Technology Inc. is an AI-driven biotechnology company based in Redwood City, California. Its core technology is AIDME (AI-Directed Molecular Evolution). Rather than a general-purpose AI SaaS product for everyday users, it is a technology platform and solution provider for synthetic biology, protein engineering, and bioindustrial use cases, aiming to use AI to support protein design, protein/genome engineering, and directed molecular evolution.
The official website describes four platforms: Polaris, for novel protein discovery, combining large-scale data analysis across evolutionary biology, structural biology, and patent landscapes; Canopus, for AI-directed design, learning, and inference, designing mutation sets and mapping protein and genome fitness landscapes; Kepler, for intelligent library creation, introducing amino acid combinations according to target mutation rates; and HVS, which emphasizes automated sampling to generate accurate, reproducible data suitable for machine learning and deep learning. Typical applications include PET plastic degradation and recycling, enzymatic deconstruction of biopolymers, therapeutic protein development, and bioindustrial enzyme engineering.
The official website does not disclose pricing, free trials, project quotation methods, delivery timelines, or contract models. It also does not state whether a self-service software portal, API, or SDK is available. As a result, it is more likely positioned as a customized R&D collaboration or platform service for enterprises and research institutions, requiring further discussion through a contact form.
Its strengths lie in covering key parts of the technical workflow, from protein discovery and AI design to mutant library construction and automated data generation. The company has also disclosed multiple PCT patents and some granted patent information in areas such as PETase and plastic degradation. The management team has experience in enzyme engineering, computational chemistry, bioinformatics, automation, and industrialization. The limitations are also clear: it does not publish model architectures, training data, performance benchmarks, customer cases, data privacy terms, or interface capabilities, making it difficult for external users to evaluate real-world effectiveness and return on investment.
It is better suited to biotechnology companies, industrial enzyme companies, and research-to-commercialization teams with specific needs in protein engineering, enzyme optimization, plastic degradation, or therapeutic protein R&D. It is not a good fit for individual users looking for a ready-to-use AI tool. The official website does not provide information on access from China, so this remains unknown; payment methods are also not disclosed. If a China-based team adopts it, they should carefully confirm cross-border network availability, contract and payment methods, compliance requirements for exporting sample/sequence data, intellectual property ownership, and whether local alternatives exist, such as synthetic biology CROs, protein design platforms, or university-industry joint laboratory solutions.
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