Uses machine learning models to predict genetic modifications that will optimize microbial hosts for the production of target molecules, significantly accelerating the design phase.
Employs robotic systems to physically construct and test thousands of genetically engineered microbial variants in parallel, generating massive amounts of empirical data.
A fully integrated facility where automated strain engineering, fermentation, and analytics are co-located, enabling rapid iteration from digital design to physical sample.
A data system that correlates genetic designs, fermentation conditions, and material properties to uncover non-obvious relationships and optimize for final product performance.
Provides expertise and processes to transition promising lab-scale strains to pilot and commercial-scale fermentation, a major bottleneck in biotechnology.
A consumer goods company partners with Zymergen to create a new, fully biodegradable film for flexible packaging. Zymergen's AI designs microbes to produce a novel polymer with the required barrier properties and mechanical strength. The resulting bio-based material offers a drop-in replacement for petroleum-based plastics, helping the company meet its sustainability goals without sacrificing performance.
An electronics manufacturer seeks a clearer, more durable optical film for device displays. Zymergen engineers a microbial pathway to produce a specific high-purity organic compound. This bio-derived material can be coated onto displays, offering improved optical clarity and scratch resistance compared to existing synthetic alternatives, enabling next-generation consumer electronics.
An agribusiness aims to develop a new, more effective biostimulant or biopesticide. Zymergen screens and designs microbes to produce beneficial metabolites that enhance crop growth or protect against pests. The resulting product is naturally derived, can have a favorable environmental profile, and offers farmers a new tool to improve yield and resilience.
A cosmetics company wants a new, sustainably sourced emollient or surfactant with unique sensory properties. Zymergen identifies or creates a microbial strain that synthesizes the target lipid or glycolipid. This provides a 'clean-label,' bio-based ingredient that aligns with consumer demand for natural and high-performance personal care products.
An industrial materials company explores entirely new polymers or additives with exceptional thermal stability or conductivity. Zymergen's platform allows for the exploration of chemical spaces not easily accessible through traditional synthetic chemistry. This can lead to breakthrough materials for aerospace, automotive, or energy applications that are both high-performing and sustainable.
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15Five operates in the people analytics and employee experience space, where platforms aggregate HR and feedback data to give organizations insight into their workforce. These tools typically support engagement surveys, performance or goal tracking, and dashboards that help leaders interpret trends. They are intended to augment HR and management decisions, not to replace professional judgment or context. For specific information about 15Five's metrics, integrations, and privacy safeguards, you should refer to the vendor resources published at https://www.15five.com.
20-20 Technologies is a comprehensive interior design and space planning software platform primarily serving kitchen and bath designers, furniture retailers, and interior design professionals. The company provides specialized tools for creating detailed 3D visualizations, generating accurate quotes, managing projects, and streamlining the entire design-to-sales workflow. Their software enables designers to create photorealistic renderings, produce precise floor plans, and automatically generate material lists and pricing. The platform integrates with manufacturer catalogs, allowing users to access up-to-date product information and specifications. 20-20 Technologies focuses on bridging the gap between design creativity and practical business needs, helping professionals present compelling visual proposals while maintaining accurate costing and project management. The software is particularly strong in the kitchen and bath industry, where precision measurements and material specifications are critical. Users range from independent designers to large retail chains and manufacturing companies seeking to improve their design presentation capabilities and sales processes.
3D Generative Adversarial Network (3D-GAN) is a pioneering research project and framework for generating three-dimensional objects using Generative Adversarial Networks. Developed primarily in academia, it represents a significant advancement in unsupervised learning for 3D data synthesis. The tool learns to create volumetric 3D models from 2D image datasets, enabling the generation of novel, realistic 3D shapes such as furniture, vehicles, and basic structures without explicit 3D supervision. It is used by researchers, computer vision scientists, and developers exploring 3D content creation, synthetic data generation for robotics and autonomous systems, and advancements in geometric deep learning. The project demonstrates how adversarial training can be applied to 3D convolutional networks, producing high-quality voxel-based outputs. It serves as a foundational reference implementation for subsequent work in 3D generative AI, often cited in papers exploring 3D shape completion, single-view reconstruction, and neural scene representation. While not a commercial product with a polished UI, it provides code and models for the research community to build upon.
