wise.io provides an extremely fast implementation of the Random Forest machine learning technique that is suitable for classifying complex, high dimensional data orders of magnitude more quickly than most alternatives. The technology was originally developed to search data generated by astronomical observations. The power of the technology is well expressed by its ability to learn and categorize handwriting within just a few minutes, compared with a week of learning using the favorite technology for this problem, the support vector machine.
I spoke with Joshua Bloom, the CEO of the company and UC Berkeley Associate Professor Astrophysics. He was keen to emphasize that the learning algorithm is just a small part of the overall model production and deployment cycle, although having a resource that executes at this speed makes many otherwise difficult problems amenable to a solution.
The company offers a SaaS facility called Machine Intelligence Engine where users upload their data, build a model and then either download it, or have it execute in the SaaS environment. Fees are levied according to the level of usage, and users typically require a period of hand-holding, which may range from a few hours to a few days. WiseRF on the other hand is downloadable and allows models to be built in-house. It comes in three flavors – Pine, Oak and Sequoia with increasing scalability and capability. A 15 day trial can be downloaded.
Applications range from OTC trading through to industrial safety, and while the accuracy of Random Forest is widely appreciated, having these very high levels of performance means that ‘real-time’ problems can be addressed.
wise.io is supported by its customers and is cash flow positive (a rare state for a startup) and will undoubtedly make a nice acquisition should the firm wish to go that way.