Automatically analyzes user sessions to identify patterns, pain points, and opportunities using natural language processing and behavioral analysis.
Provides access to a vetted panel of participants matching specific demographic and behavioral criteria for rapid testing.
Enables moderated and unmoderated remote testing sessions with screen recording, audio capture, and task completion tracking.
Seamlessly connects with popular design tools like Figma, Sketch, and Adobe XD to test interactive prototypes.
Provides shared dashboards where team members can tag, comment, and analyze findings together in real-time.
Generates comprehensive reports with key findings, metrics, and video highlights that can be shared with stakeholders.
Product designers use Validately to test interactive prototypes with real users before engineering begins. By uploading Figma or Sketch prototypes, designers can identify usability issues, confusing navigation patterns, and missing features early in the process. This prevents costly rework during development and ensures the final product aligns with user expectations and needs from the outset.
Marketing and product teams employ Validately to test website redesigns with target audiences. They create tasks for users to complete on new designs, measuring success rates, time on task, and user satisfaction. The AI analysis helps identify which design elements work well and which cause confusion, enabling data-driven decisions about layout, content placement, and user flow before launching changes to the public.
Product managers use Validately to test multiple feature concepts with users to determine which ones provide the most value. By presenting different solutions to the same problem, teams can gather quantitative and qualitative data about user preferences. This helps prioritize the product roadmap based on actual user needs rather than assumptions or internal opinions.
UX researchers conduct comparative studies using Validately to understand how their product stacks up against competitors. They create identical tasks for users to complete on multiple products, then analyze performance differences, user preferences, and pain points. This provides actionable insights about where to focus improvement efforts and what competitive advantages to emphasize.
Design teams use Validately to test products with users who have diverse abilities and needs. By recruiting participants with specific accessibility requirements, teams can identify barriers and improve inclusive design. The platform's recording capabilities capture both verbal feedback and interaction patterns that reveal accessibility challenges that might not be caught through automated testing alone.
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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.
