Figr AI: UX Agent for Product Teams — Learns your product. Thinks through UX
Learns your product. Thinks through UX
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What inspired me to build Literios was a recurring frustration while working with research papers. Finding the right papers and managing them efficiently often took more time than the actual research.
The core problem was not the lack of information, but the difficulty of identifying which papers were truly relevant. Researchers also spend a significant amount of time downloading open access papers from multiple sources and manually collecting citations. These tasks are repetitive, time consuming, and take focus away from deeper research and analysis.
The initial goal was to reduce friction in the literature review process by helping users quickly narrow down the most relevant papers. As development progressed, the approach evolved naturally. Once relevance was addressed, it became clear that access and organization were equally important. This led to features that allow downloading open access papers and collecting citations more easily.
Over time, the focus expanded from simply finding papers to supporting the early stages of the research workflow. This includes discovery, selection, and preparation for writing. Continuous feedback helped shape the product with an emphasis on practical usefulness rather than unnecessary complexity.
Literios continues to evolve, but the motivation remains the same. It aims to help researchers spend less time managing papers and more time thinking, analyzing, and creating knowledge.
