AWS Startups Blog

Category: Analytics

How Timehop Developed the World Class Ad Platform Nimbus with Support from AWS

How Timehop developed the world class ad platform, Nimbus, with support from AWS

We recently sat down with the Timehop and Nimbus CEO, Matt Raoul, as well as two talented team members, David Leviev, VP of Programmatic Product Development, and Mark Laczynski, Senior Cloud Architect to discuss the obstacles the company has faced using third-party ad serving platforms that led to the in-house creation of Nimbus. They shared their challenges and revealed how they leveraged AWS solutions to optimize the development of Nimbus within Timehop, and not only improved the quality of ad servicing to their users, but also increased overall ad revenue.

Next Generation Data Management for Clinical Trials & Research Built on AWS

Cumbersome, disparate data sources in highly regulated environments have historically obstructed longitudinal patient views in clinical research. To help clients generate maximum evidence from trials, Precision Digital Health (PDH) developed a cloud-based platform capable of integrating and harmonizing disparate data assets in the R&D and life sciences industry.

Canasta Rosa Uses AWS to Steer Unique Small Businesses to Success

In Latin America, small businesses and micro-entrepreneurs face significant economic barriers. To combat issues of limited technological knowledge, fears about the process of launching an online store, and uncertainty when it comes to choosing the right platform, Mexico-based Canasta Rosa (Spanish for Pink Basket) is guiding small businesses to success. Spearheaded by CEO Deborah Dana, the startup has a clear purpose: To empower micro and small entrepreneurs to build and scale their businesses.

Car Sales Startup Kavak Kicks ML into High Gear with AWS and a Serverless Architecture

Founded in 2016, Kavak is the digital platform that’s making it easier than ever to buy and sell cars. The Mexico City-based founded startup recently achieved “unicorn” status after reaching a $1.15 billion valuation, the first tech company in the country to do so. As Kavak expands its operations to Argentina and sets sights on Brazil, we sit down with Vice President of Data Science, Anders Christiansen, to chat about how machine learning and AWS serverless services helped build the engine behind the company’s ever-improving workflow.

Roadmap Software Startup Aha! Uses Amazon Athena to Ensure Fast Support Responses

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.

Syllable Automates Healthcare’s Frontline with AWS

Given the times we are living in, healthcare organizations are going through digital transformation at a faster rate than ever before. And that was before the pandemic. Almost overnight, the healthcare system was hit with a new wave of demand, a lack of resources, and the need to separate the non-urgent services from the essential. Syllable was perfectly poised to help. Founded in 2016, the Bay Area-based company works on automating the “frontline” of healthcare, or the first point of contact between patients and providers.

BondEvalue: Disrupting Regulated Bond Markets with Cloud Strategy

Bond markets are huge, far larger than stock markets, with over eight million securities in contrast with only six hundred thousand stocks. They are also far more complex than equities. Minimum investment of $200,000 for most popular bonds means most non-institutional investors cannot invest in bond markets! That’s where fintech and blockchain startup BondEvalue comes in.

tow men sitting in an office having a discussion about 1mg

1mg: Building a Patient Centric Digital Health Repository – Part 2

Utkarsh Gupta, Lead Data Scientist at 1mg.com walks us through how the healthcare startup is building a patient-centric digital health repository. In part 2 of this series, he discusses how the infrastructure described above can be used for large scale machine learning applications and the ways to deploy them in production.