It’s trendy and fashionable for software companies in 2017 to provide three things in their application: a) machine data as a foundation; b) user-friendliness, especially for neophytes; and c) speedy performance.
Information finder Insight Engines checks all three boxes. This is a San Francisco-based startup that claims its app enables anyone to ask questions of its machine data core and get answers and/or insights in seconds.
Oh, and there’s yet another benefit: This natural-language processing software fills much of the void for companies who are unable to hire data scientists, a job classification whose members are few and far between in the IT world. This is because Insight Engines can find, display and help triangulate various data streams, logs and stores to tell stories that few people are qualified to tell.
A whole slew of IT experts believes Insight Engines can do what it says it can do. The company on July 20 announced that it has raised $15.8 million in Series A funding led by August Capital, with participation from Splunk, Real Ventures, Data Collective and industry luminaries Erik Swan and Simon Crosby.
August Capital General Partner David Hornik, an original investor in Splunk, and Swan, a co-founder and the former CTO of Splunk, will join the board.
In less than a year, Insight Engines has gained a fair amount of market traction within Fortune 500 and major government organizations since releasing its first product, Insight Engines Cyber Security Investigator for Splunk, in fall 2016. The company said the funding will be used to accelerate its product roadmap and expand its sales and marketing teams.
Many enterprises have discovered that the value of big data is limited because highly-trained analysts need to craft complex, proprietary queries in order to creatively search and visualize machine data. These languages are difficult to learn and use, which results in a small subset of technical employees being able interact with a subset of the machine data.
CEO Grant Wernick and CTO Jacob Perkins (author of "NLTK Cookbook" and contributor to O'Reilly's "Bad Data Handbook") started Insight Engines in 2015 to open the machine-data door to a much larger subset of line-of-business employees.
"We started this company because every organization is making massive investments to harness their machine data but they all suffer from the same hiring, training and accessibility issues around it. We enable companies to expand their hiring pool, simplify training and accelerate their ability to extract knowledge from their data," Wernick said.
"Today our technology is primarily used for security purposes, transforming novices into ninja analysts and enabling the most advanced analysts to move faster. Long term, we will apply similar innovations to solve problems beyond security, such as IT operations, application delivery and business analytics."