Software vendors that are looking to accelerate their path to AI need to take advantage of the AI already in analytics platforms. Gartner believes that the future of analytics is augmented. That is, analytics will be AI-driven and all end-to-end use cases will be automated. I also believe it won’t be long before analytics is no longer on our desktops - instead it’ll be embedded in applications.

If, as we saw in part one of this series, 77% of businesses are 'definitely not' or 'probably not' using analytics to its full extent and the adoption rate of analytics platforms is an abysmal 32%, something drastic needs to happen. Can the era of augmented analytics with its machine learning and AI fix this adoption issue?

If you’ve got an app that keeps going down for no apparent reason, don’t worry: this quick and easy guide will give you the tools to get it up and running smoothly. If you’re not from the tech world yourselves, you probably think us programmers get everything right all the time. That everything in our world is so cutting-edge it can slice through ice, and app crashes are practically an alien concept for us.

Can we fix the plague in analytics with AI? Every Business Intelligence (BI) and analytics vendor is integrating a form of artificial intelligence (AI), machine learning algorithm (ML), and natural language generation (NLG) into their products. 'Augmented analytics', is the hot new topic and full of hype right now, but can it fix the fundamental flaw that has plagued BI tools for decades - adoption?

Last month, Bugfender turned four years old. We didn’t throw a massive party to celebrate the birthday, but we all reflected with pride on the amazing journey we’ve been on. In celebration though we have setup an affiliate program, allowing you to share the love, earn some cash rewards – and improve the quality of apps all over the world! Find out more in our blog post.

Self-driving vehicles, weather forecasting drones, fulfilment robots and robotic surgery are already transforming the lives of millions of people. It is deep learning computer vision (DL CV) — visual sensors coupled with the ability to make instantaneous, human-like sense out of streaming video — that make these applications possible. One might think that acute focus on DL CV applications would be sufficient to yield the necessary breakthroughs and successful industry applications.

Until late last year, Rainforest ran most of our production applications on Heroku. Heroku was a terrific platform for Rainforest in many ways: it allowed us to scale and remain agile without hiring a large Ops team, and the overall developer experience is unparalleled. But in 2018 it became clear that we were beginning to outgrow Heroku.

New Relic has changed the game in the application performance monitoring market. It’s heading towards $1 billion in revenue and has already raced past 17,000. Now we want to explain how to integrate this amazing product with Bugfender to ensure end-to-end traceability for your mobile app.