FiglinQ
Collaborative platform for management, analysis, visualization and publishing of (research) data.
| Date | Investors | Amount | Round |
|---|---|---|---|
| - | investor investor | €0.0 | round |
N/A | Spinout | ||
| Total Funding | 000k | ||
| USD | 2022 | 2023 |
|---|---|---|
| Revenues | 0000 | 0000 |
| EBITDA | 0000 | 0000 |
| Profit | 0000 | 0000 |
| EV | 0000 | 0000 |
| EV / revenue | 00.0x | 00.0x |
| EV / EBITDA | 00.0x | 00.0x |
| R&D budget | 0000 | 0000 |
Source: Dealroom estimates
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FiglinQ is a dynamic startup that operates in the research data management and publication market. The company provides a comprehensive platform designed to store, analyze, visualize, and publish research data seamlessly. FiglinQ serves a diverse clientele, including academic researchers, students, and professionals who require robust data management and analysis tools.
The core of FiglinQ's business model revolves around offering a cloud-based platform that integrates with advanced programming environments like Python, R, and Matlab. This allows users to perform sophisticated data analysis and upload their results and visualizations directly to the platform. The platform supports a collaborative approach, making it easier for teams to work together on data-driven projects and access centralized course resources.
FiglinQ makes money through subscription fees for access to its platform. Users can choose from various pricing tiers based on their needs, ranging from individual plans for students to more comprehensive packages for institutions and research organizations. Additionally, FiglinQ may generate revenue through premium features and services, such as advanced data analytics tools and enhanced publication options.
The platform's standout feature is its ability to create "smart manuscripts" and reports. Users can embed interactive charts, figures, and underlying data directly into their publications, making it easier to share and publish research findings. This functionality supports the principles of FAIR data (Findability, Accessibility, Interoperability, and Reusability), ensuring that research data is transparent, reproducible, and open.
In summary, FiglinQ is revolutionizing the way research data is managed and published by providing an integrated, user-friendly platform that supports advanced data analysis and collaborative work. Its focus on accessibility and interoperability makes it a valuable tool for anyone involved in data-intensive research.
Keywords: research data management, data analysis, visualization, publication, cloud-based platform, Python, R, Matlab, collaborative, FAIR data.