Fred - The User Research Shepherd
The platform for user research, analysis, and recruitment.
160 followers
The platform for user research, analysis, and recruitment.
160 followers
Fred streamlines the entire UX research workflow from planning to actionable insights. With powerful features like thematic analysis, integrated tester panels, collaborative reporting, and flexible mixed-method capabilities, Fred empowers teams to efficiently create exceptional user experiences.
Products used by Fred - The User Research Shepherd
Explore the tech stack and tools that power Fred - The User Research Shepherd. See what products Fred - The User Research Shepherd uses for development, design, marketing, analytics, and more.
Productivity 2
Productivity 2
MirotalkSimple, Secure, and Fast. Mirotalk is Powered by WebRTC.
5.0 (1 review)
We chose MiroTalk because it gave us a strong open-source foundation for building UserSphere, our live and replay-based research session layer. It lets us move faster on real-time interviews, collaboration, recording, and session analysis while keeping full control over the experience we need for UX research workflows.
FigmaThe collaborative interface design tool
4.9 (1.5K reviews)
Figma served as our essential design tool for prototyping, collaboration, and visualizing user interfaces. Figma's real-time collaboration features allowed our design and development teams to work together seamlessly, iterate quickly, and maintain consistency across the project. By enabling us to create interactive prototypes and gather user feedback early in the design process, Figma played a crucial role in ensuring that Fred's user experience was intuitive and user-centered from the start.
Design & Creative 1
Design & Creative 1
FlowbiteOpen-source ecosystem built on top of Tailwind CSS
4.9 (12 reviews)
Flowbite's customizable and accessible components allowed us to create a polished, consistent user interface that aligns with modern design standards. This saved us time and effort in building UI elements from scratch, enabling us to focus on enhancing Fred's functionality and user experience.
LLMs 1
LLMs 1
NVIDIAThe official handle for NVIDIA.
5.0 (27 reviews)
We chose NVIDIA because we are part of the NVIDIA Inception Program and use their Nemotron 120B model to power advanced some of the AI features in Fred. Their ecosystem gives us the performance, model quality, and scalability we need to build reliable research intelligence workflows.
Engineering & Development 2
Engineering & Development 2
AWSAWS offers reliable, scalable, and inexpensive cloud.
5.0 (236 reviews)
We chose AWS because it gave us the best balance of scalability, reliability, and data control from day one. Fred handles research data, media, analytics, and AI workflows, so we needed infrastructure that could grow with us without compromising performance or security.
Next.jsCreate web applications with the power of React components
5.0 (476 reviews)
Next.js allowed us to implement server-side rendering, optimize performance, and manage dynamic content seamlessly. Its built-in features for routing, API integration, and static site generation made the development process smoother and more efficient, enabling us to focus on building a robust user experience for our platform.
General 2
General 2
WebGazer.jsEye tracking on the browser
We chose WebGazer.js because its research papers and open work gave us a strong technical foundation to build our own eye-tracking system. It helped us move faster on browser-based gaze tracking while giving us the flexibility to adapt the technology to UX research, session analysis, and heatmap workflows inside Fred.
MiroTalkMiroTalk WebRTC AI next generation video conferences.
5.0 (1 review)
We couldn't have built Fred The UXR Shepherd without using MiroTalk because it provides a crucial platform for conducting user interviews and web conferences. MiroTalk's seamless video communication capabilities allow us to engage with users directly, gather real-time feedback, and collaborate effectively with our team, regardless of location. This integration ensures that our user research is thorough and that we can iterate on Fred based on actual user insights, which is vital for developing a user-centered tool like Fred.