We can already witness how AI software is supplying enterprises around the globe with automation for low-value and repetitive tasks. In turn, this frees up engineers and other skilled workers to get on with the tasks that have a much higher value in the overall scheme of design to production. Thus, machine learning (ML) is going to become — if it’s not already — an important tool in tracking patterns in data, inevitably helping make correct engineering judgments and a greater ROI.
The Deep Tech Insider will now briefly highlight five doing just that, making engineering decisions, well, easier to make and justify.
Logz.io is a cloud observability platform for modern engineering teams. The Logz.io platform consists of four products — Log Management, Infrastructure Monitoring, Distributed Tracing, and Cloud SIEM — that work together to unify the jobs of monitoring, troubleshooting, and security. It empowers engineers to deliver better software by offering the world’s most popular open-source observability tools in a single, easy-to-use, and powerful tool purpose-built for monitoring distributed cloud environments.
Headquartered in Boston, Massachusetts, Logz.io was founded in 2014 by Tomer Levy and Asaf Yigal and has raised an impressive $121 million in funding over seven rounds.
Rainforest is changing the way QA is done in an era of continuous delivery. Founded by Fred Stevens-Smith and Russell Smith, its on-demand QA solution improves the customer experience by enabling development teams to discover significantly more problems before code hits production. Hundreds of companies including Adobe, Oracle and Solarwinds use Rainforest to automate their QA testing process and easily integrate it with their development workflow via a simple API.
Headquartered in San Francisco, Rainforest is a 2012 Y Combinator graduate that has raised some $41.2 million in funding over nine rounds backed by the likes of Bessemer Venture Partners and SVB Capital among others.
Kite’s software is transforming the world, but it can’t write it fast enough. Despite increases in the number of software engineers being trained and advances in developer productivity, demand for software continues to outstrip supply. Nobody can hire software engineers fast enough, and this is an important limit on growth worldwide. So, how can Kite solve this problem?
By increasing developer productivity. Coding today is very repetitive, which is why it is using ML to eliminate the repetitive parts of programming — to make developers much more productive. And as a result, it is removing a huge bottleneck for progress in the world. Kite released Line-of-Code Completions for Python in January 2019, harnessing advanced statistical modelling to incorporate context and complete up to full lines of code as Python programmer type. This is just one more step in the Staircase of Intelligence that will lead the startup towards its vision of building the future of programming.
Founded in 2014 by Adam Smith, the San Francisco-based company has raised approximately $17 million in funding over two rounds.
Founded way back in 1984 by Doug Lenat, Cycorp is an Austin-based provider of semantic technologies that bring a new level of intelligence and common-sense reasoning to a wide variety of software applications. The Cyc software combines an unparalleled common-sense ontology and knowledge base with a powerful reasoning engine and natural language interface to enable the development of novel knowledge-intensive applications.
Cycorp has raised approximately $7 million in funding.
Diffbot is a world-class group of AI engineers building a universal database of structured information to provide knowledge as a service to all intelligent applications. Whether customers are building an app that uses web content, an enterprise business application, or a smart robotic assistant, Diffbot has a solution. Thousands of leading companies rely on Diffbot data for their enterprise and consumer applications.
Based in Menlo Park, California, Diffbot was founded in 2011 by Michael Tung and Leith Abdulla and has raised approximately $13 million in funding to date.