Category: Startup

Aha! is a leading roadmap software provider, helping more than 400,000 users build products and counting north of 5,000 companies as customers. Founded in 2013 with an entirely distributed team, the company puts customer needs at the heart of its business model. Read how the company was able to drive results by migration to Amazon Athena from BigQuery.

In the final post of the Founder Sales series, AWS Startup Advocate Mark Birch shares how to avoid the 11th hour close.

In part 11 of the Founder Sales Series, AWS Startup Advocate Mark Birch shares some of the more common sticking points and areas of caution when it comes to legal side of closing deals.

Since 2015, Holo-Light focuses on immersive software and technologies. In augmented and virtual reality, they see a big driver for global digitization and a new way of experiencing and interacting with content – from the industrial sector to entertainment and gaming. Here’s what they’re doing.

In part 10 of the Founder Sales series, AWS Startup Advocate Mark Birch walks through the common mistakes that can lead to a good deal unraveling and how to address them.

Build a better way to work. Amazon Honeycode gives you the power to build apps for managing your team’s work. No programming required. Here’s how it works.

Drawing from his experience at three software startups that partnered with AWS Marketplace over the last decade, Ahana Co-founder and CEO Steven Mih has put together some best practices to help make your AWS Marketplace listings successful. To illustrate the point, he’ll use examples here at Ahana, who offers a managed service for Presto in AWS.

After you have had successful preliminary sales meetings, the next step is to build upon these initial meetings to develop internal support for your solution and ensure your efforts lead to a signed deal. AWS Startup Advocate Mark Birch walks through how to do so in part 9 of the Founder Sales series.

For most machine learning startups, the most valuable resource is time. They want to focus on developing the unique aspects of their business, not managing the dynamic compute infrastructure needed to run their applications. Productionizing machine leaning should be easier, and that’s where AWS comes in. In this blog post and corresponding GitHub repo, you will learn how to bring a pre-trained model to Amazon SageMaker to have production-ready model serving in under 15 minutes.

Overnight, the COVID-19 pandemic reshaped how and where Americans work. By June, according to a survey from Stanford researchers, 42% of the U.S. labor force was working from home full time, with millions more not working at all. For employers, that shift has led to new challenges as they navigate an unprecedented economy. One big question: what to do with all the empty offices?