AWS Startups Blog

No matter what market you’re in, successful startups all have a few things in common—a passion and commitment for what they’re doing, a great story to tell and a laser-like focus on customer needs. Dataiku has taken the data and AI world by storm—transforming from French startup to global unicorn in just seven years. The team’s journey began with a passion for data and machine learning (ML) and a quest to bring everyday artificial intelligence (AI) to companies of all sizes and sectors.As a founder, your path will of course be different from Dataiku’s, but they can show you what to look out for and provide advice to aid and speed your progress.

What do you do if you don’t have the resources, time, or funds to self-manage a database? Use Amazon Relational Database Service (RDS)! Amazon RDS allows you to set up, operate, and scale a relational database in the cloud with just a few clicks. It removes inefficient and time-consuming database administrative tasks without needing to provision infrastructure or maintain software. And, with the new AWS Database Plug & Play Program, you’ll get a packaged bundle of AWS advisory time, architecture and prototyping patterns, AWS usage credits, and pathways to go-to-market acceleration programs to help further ensure your teams can focus on value-generating work.

Originally, Fyle’s Data-Extractor service relied on an external service provider for optical character recognition (OCR) and Fyle’s internal machine learning algorithm to detect amount, category, date, currency, and vendor information. Unfortunately, they were receiving some feedback from customers that their tool wasn’t very accurate. As you can imagine, this isn’t the best place to be, so they rewrote their Data-Extractor service to use Amazon Textract because of its intuitive web console for APIs, which allowed them to test APIs in real-time with personalized input. This let them quickly try out an Amazon Textract API, which helped them achieve their goal of turning around a solution in two months. After implementing their new solution, Fyle saw 51.7% improvement in accuracy for the Data-Extractor service.

Understanding your data types and their sensitivity levels ensures that your startup stays ahead of unintended data use or disclosures and satisfies compliance requirements. By identifying the data you have and implementing appropriate, automated controls, you can meet these requirements more easily, while also improving your security posture. To get you started, this post provides four simple steps to simplify and automate the data classification process for your startup.

By using Serverless on AWS to scale their infrastructure, the cinch team was able to focus their cognitive load on improving the platform, quickly release new features, and re-build existing ones based on real world customer insight. With their new architecture, cinch was able to pivot their business to the new model in 6 months, increase traffic by 2.5x (6,000 to 16,000 requests per minute), and reduce latency. They went from hundreds of cars sold within days, and grew by a factor of 100x within a few weeks.

It’s almost the most wonderful time of the year again: AWS re:Invent is just around the corner. And while we’d love to hang out with you in Las Vegas from November 28 through December 2, never fear if you can’t attend in person. You can still get everything re:Invent has to offer by attending virtually. (Well, except for the slot machines and general Vegas-fueled sensory overload, of course!)

It has been an amazing first 12 months for our AWS Startup Loft Accelerator program. So far, we have helped over 275 early-stage (two years and under) companies with technical and business expertise, tailored training, and mentoring across Europe, the Middle East, and Africa (EMEA). Every month, we welcome 30 new startups into the 10-week virtual program. They learn together and form a supportive community of innovative entrepreneurs. In this post, we hear from the companies themselves about their participation in the program.

AWS re:Invent 2022 is fast approaching, and we can’t wait to see you in Las Vegas from November 28 through December 2! As usual, these four days will be jam-packed with activities, networking events, inspiring keynote speakers, breakout sessions that will allow you to connect with fellow attendees, interactive workshops, and more.

As with all best forms of innovation, great ideas stem from true need. In Mexico, there is a need for an equitable, efficient, and sustainable healthcare system. Latino startup founders are addressing this need and advancing healthcare equity by leveraging artificial intelligence (AI) to drive better patient outcomes.

Pieces Technologies, Inc. (Pieces), a healthcare and life sciences startup, is blazing a trail in the predictive AI/ML space. Pieces is a software as a service (SaaS)-based AI platform integrated into a hospital’s electronic health record (EHR). Their mission is to improve care by providing clinical insights along the patient journey. They offer predictions of health events such as projected discharge dates, anticipated clinical and non-clinical barriers to discharge, and risk of readmission, before they occur. Pieces also provides insights to healthcare providers in natural language, and optimizes the overall clarity of the patient’s clinical issues so care teams can work more efficiently.