Insight Engines Snags $15.8M
SAN FRANCISCO, CA, Insight Engines, the company that lets anyone ask questions of machine data and get insights in seconds, today announced that it has raised $15.8 million in Series A funding.
The round was 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.
Insight Engines has quickly gained market traction within Fortune 500 and major government organizations since releasing its first product -- Insight Engines Cyber Security Investigator for Splunk -- in the Fall of last year. The funding will be used to accelerate its product roadmap and expand its sales and marketing teams.
Hornik said: "Insight Engines is addressing a massive, multi-billion dollar market opportunity and solving meaningful customer pain with a truly differentiated product. Their unique technology and strong value proposition is reflected in their fast market traction. Insight Engines is already addressing important challenges for some of the biggest organizations in the country."
Swan said: "I've been in the Valley a long time, and it's rare I've seen a company with this kind of traction and revenues at this stage which is why I was stoked to invest and join the board. Insight Engines is solving a real problem and has awesome technology and happy customers. I see a lot of similarities to Splunk which is now doing close to a billion in revenues."
Organizations have found 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.
Grant Wernick (CEO) and Jacob Perkins (CTO and author of "NLTK Cookbook" and contributor to O'Reilly's "Bad Data Handbook") founded Insight Engines in 2015 to unlock the value of machine data to make it accessible and actionable to everyone, from an analyst to an executive. Only with Insight Engines' natural language processing (NLP) technology can everyone in the organization ask direct questions in plain English of their machine data and get back valuable answers in seconds. Users no longer need to craft complex, optimal big data queries -- Insight Engines frees users' time to analyze more and search less.
"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," said Grant Wernick, co-founder and CEO of Insight Engines. "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."
About Insight Engines
Insight Engines enables organizations to unlock the value of machine data so it becomes accessible and actionable to anyone in an organization, from an analyst to an executive. Its unique and powerful natural language search technology enables everyone to ask the questions that matter in plain English and generates highly optimized queries against their data in real time, eliminating the need to spend years becoming an expert in complex search languages and days crafting queries. Customers include the Fortune 500 as well as major government organizations. Insight Engines is backed by August Capital, Splunk, Real Ventures and Data Collective and is headquartered in San Francisco, CA. For more information, visit http://www.insightengines.io or follow the company on Twitter @InsightEngines.
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