> For the complete documentation index, see [llms.txt](https://handbook.redivis.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://handbook.redivis.com/company/our-story.md). # Our story ## We began with one goal: to democratize data. Understanding human-centered data is profoundly important; it captures how our societies succeed and how they ought to improve. But all too often, the value of data is unrealized because of siloed systems and inflexible tools. In the spring of 2015, we set out to make such data more available. ## We started by making data more visual Data is useless if it can’t be understood. A billion temperature measurements are essentially incomprehensible, but a time-series choropleth on a map of the world can tell us an important story about climate change. Redivis began by helping researchers [visualize](https://www.wfns.org/menu/62/2016-neurosurgical-capacity-and-access-by-country) their data — both for them to better understand and to best articulate these data to a broader audience. [This](https://jamanetwork.com/journals/jamasurgery/fullarticle/2546329) [work](https://www.journalacs.org/article/S1072-7515\(16\)31039-0/abstract) [was](http://www.jmir.org/2018/5/e186/) [published](https://gh.bmj.com/content/2/2/e000226) [across](https://www.journalofsurgicalresearch.com/article/S0022-4804\(17\)30668-6/abstract) [multiple](https://www.sciencedirect.com/science/article/pii/S187887501830069X) [papers](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5463808/), and most importantly, gave us early insight into the data-driven research process. ## Then we tackled data management. Data visualization is essential to their communication, but it requires that we have data. And that they’re reasonably clean. And what about restricted data? Metadata? Big data? It was these challenges that excited us as we began our partnership with the [Stanford Center for Population Health Sciences](http://med.stanford.edu/phs.html) in 2016. With their rich and varied datasets and community of talented researchers, the center was the perfect partner to learn and develop novel solutions for data administration alongside reproducible tools for data analysis. ## Today, we are building a collaborative community… As more organizations and researchers join Redivis, we continue to strive to connect the various nodes and incentives in the data ecosystem. We endeavor to reduce friction at every step of the research process, and minimize the roadblocks to working with data. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://handbook.redivis.com/company/our-story.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.