An AI-powered assistant that understands research context, answers scientific questions, and provides relevant literature references. It can interpret complex queries and generate hypothesis-driven responses.
End-to-end data processing system that automatically cleans, transforms, and analyzes research data using appropriate statistical methods and machine learning algorithms.
Identifies connections and patterns across different research domains by analyzing disparate datasets and literature sources simultaneously.
Comprehensive visualization interface that presents research findings through interactive charts, graphs, and summary reports with drill-down capabilities.
Shared workspace where research teams can collaborate on projects, share findings, assign tasks, and track progress in real-time.
Automatically scans, summarizes, and synthesizes relevant scientific literature based on research questions and uploaded data.
University researchers and PhD students use WhiteRabbit AI to accelerate literature reviews, analyze experimental data, and generate research hypotheses. The tool helps identify relevant studies, process complex datasets, and suggest statistical approaches, reducing weeks of manual work to days. Researchers benefit from faster insight generation while maintaining academic rigor through proper methodology selection and citation management.
Biotech and pharmaceutical companies employ WhiteRabbit AI to analyze clinical trial data, identify potential drug candidates, and understand disease mechanisms. The platform processes genomic data, patient records, and chemical compound libraries to reveal patterns that might indicate therapeutic potential. This accelerates early-stage discovery while reducing costs associated with manual data analysis and literature review.
Interdisciplinary research teams use the platform to bridge knowledge gaps between different scientific domains. By analyzing data and literature from multiple fields simultaneously, WhiteRabbit AI identifies connections that individual domain experts might miss. This is particularly valuable for complex problems like climate change research, public health initiatives, or materials science where multiple disciplines intersect.
Scientists and institutions use WhiteRabbit AI to strengthen grant applications by identifying relevant literature, analyzing preliminary data, and highlighting research gaps. The tool helps create compelling narratives with data-driven justifications, increasing the likelihood of funding success. It also assists in identifying potential collaborators and benchmarking against existing research in the field.
Technology and manufacturing companies leverage WhiteRabbit AI to analyze patent databases, technical literature, and experimental data to identify innovation opportunities. The platform helps R&D teams stay current with scientific advancements, analyze competitor research, and identify white spaces for new product development. This accelerates innovation cycles while reducing the risk of redundant research efforts.
Sign in to leave a review
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.
