Our Story
- Travis E. Oliphant
- Sep 12, 2018
- 5 min read
At Quansight we connect companies with communities of experts that build and maintain open-source software to help you organize and analyze your data. Software such as NumPy, Pandas, Arrow, XND, PyViz, Altair, Dask, Numba, Jupyter, Scikit-learn, Chainer, PyTorch, and Tensorflow delivers you the latest advances in software engineering, data management, data visualization, machine-learning, and artificial intelligence. Using open-source software is a powerful advantage and will save you millions of dollars when you let us help connect you with community to:
Prioritize your needs.
Hire from the best talent.
Maximize your support.
Minimize your risk of obsolescence.
Quansight works directly with open-source communities to ensure the software you rely on will continue to be innovative, maintained, and supported.
We are a world-wide, full-service, open-source organization with experienced engineers and architects who have deep ties to the community around Python and machine learning. We continue to innovate on the next great open source technologies while helping organizations and entrepreneurs build impactful solutions. Our management team at Quansight built Continuum Analytics and used that company to launch both NumFOCUS and Anaconda, Inc. Quansight now partners with Anaconda, NumFOCUS, and other technology providers to create powerful, connected solutions for you.
We consult with you to solve your data architecture, data engineering, data visualization, and data migration problems choosing from the latest open-source, cloud, and commercial technologies. We train the next generation of data experts and provide training and mentoring to your organization and help you find talent. We have an innovative research and development lab dedicated to array-oriented and data-oriented computing that helps provide stable employment to talented developers who continue the community-driven, open-source enthusiasm that has produced so much for the world. We have a small venture fund to encourage entrepreneurs in starting companies that are based on open-source and also give back to open source in meaningful ways.
Our Motivation
We do all of these things because we are committed to human progress and knowledge advancement. We believe open-source represents an important innovation in planetary cooperation that we continue to augment. We believe that open-source is the right foundation for commercial software and continue to invest in maintaining existing open source while also developing new ideas in open source communities. Commercial products, services, and solutions can and should be built on open source foundations. This happens best if 1) developers steeped in community practices also become deeply aware of company needs and 2) companies cooperate with open-source communities to coordinate plans and provide aligned incentives.
Quansight exists to ensure this connection happens using lessons learned from over 20 years in the business. To understand my personal commitment, it may help you to understand my history and motivations.
Science, Open Source, and Entrepreneurship
Twenty years ago this month I was a graduate student at the Mayo Clinic awaiting the birth of my third daughter. The year before I was searching for a way to write high-level analytics code to aid my biomedical imaging research and discovered Python with its nascent array package called Numeric. Now, a year later, I was staying up late after classes and work writing documentation for the UFunc object of Numeric. (The UFunc object provides fast compiled functions over N-dimensional arrays of data.) It was tedious work, but I found joy in understanding in detail how things worked and trying to explain it to save others' time while exercising my C/C++ knowledge. I was also in the middle of releasing my first Python extension called "numpyio" which enabled reading raw binary data directly into memory without first going through intermediate Python objects like strings and lists.
As a scientist, I loved the community that surrounded open-source, and I was getting my first taste of the engaging feedback, the strive for excellence, and the work-ethic embraced by the Python and Unix communities I was exploring. I was meeting people vicariously all over the world and feeling a kinship that gave me hope for humanity and the planet. It was a wonderful time. We were passionate pioneers trying to make the world a better place. As the father of a growing family, I was also committed to earning money for their needs. The $18,000 / year my wife and I were grateful for as a graduate fellow would not sustain us for very long. How could we pay for our children's current and future needs while giving away my intellectual work?
Many have asked this same question, and many still do. Researching this question opened up a world of additional discovery for me as I consumed books and articles on markets, economy, and how to combat poverty in general. I discovered the importance of voluntary exchange, property-rights, capital savings and investment, and the critical role of entrepreneurship. All of this study would guide my future initiatives.
Origins of NumPy
After my graduate work, I spent 7 years as a professor of electrical and computer engineering at Brigham Young University (BYU). I continued to develop on the efforts I started in graduate school with "numpyio" that grew into multipack in 1999 which then folded into SciPy in 2001. In 2005, I was watching the young array-oriented computing community in Python divide into factions due to the limitations of Numeric and a new array initiative called Numarray. I spent 18 months writing NumPy to unify those libraries, essentially sacrificing my opportunities at tenure by spending more time innovating in software rather than publishing papers.
After starting SciPy and then writing NumPy, I began experimenting with entrepreneurship both fund-raising for my research lab and self-publishing the book "Guide to NumPy" to raise funds for my lab and pay graduate students who continued to contribute to SciPy. Over time, I inexorably felt drawn from my pew in the cathedrals of learning into the fast-pace world of business, and in August of 2007, I left BYU and moved to Austin, Texas to join Enthought, Inc. I had previously collaborated with Enthought in producing SciPy. Even though I left my formal academic career, I never lost the curiosity and enthusiasm for learning that drove me into science and higher-learning in the first place.
Starting Anaconda
NumPy and SciPy grew in popularity during the next several years while I worked as a consultant building custom GUI applications around NumPy/SciPy and learned more about computer science, software engineering, project management, and business operations. After seeing the challenges of deploying the useful array-computing capabilities of NumPy and SciPy at scale, I co-founded Anaconda (as Continuum Analytics) in 2012 with Peter Wang to tackle these head on and get experience with a venture-backed business.
Peter and I worked with Matt Harward, Ashley Baal, and Doug Pennock and many talented developers and other contributors to grow our young company and find a scalable product and business model which became Anaconda, Inc. Early in our history we also funded and organized the first PyData meetings and conferences and sponsored the staff of NumFOCUS which I had also founded along with 4 other community leaders in late 2011.
Quansight Beginnings
Along the way we discovered several other working business models around open-source and worked closely with other talented engineers and granting agencies to produce innovative open source such as Conda, PyViz, Numba, Dask, Dask-ML, Bokeh, JupyterLab, and Intake. As soon as we found talented leadership to continue to shepherd and grow the Anaconda opportunity, Matt Harward and I started Quansight, collaborating again with Doug Pennock and Ashley Baal to help grow our management and operations.
At Quansight we are again growing the innovation engine that drove so many advances at Continuum Analytics. We have learned important lessons from our experiences that allow us to deliver more value to our customers, colleagues, investors, and partners. We look forward to the future solutions we will build together!
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