A connected home health platform that provides a medical alert device older adults actually want to wear.
Lively brings dignity to how we care for our elders, and adds creativity to the ways families share their lives with each other.
Lively Internet of Things, mHealth
Keith Dutton, Iggy Fanlo, David Glickman
$7.3 M in 2 rounds
San Francisco, CA
2012 - 2015
Backend, Frontend, Deploy Automation & Data Analysis
When Lively contacted us they had this great product idea, a co-founders team with solid entrepreneurial background and not a single LOC. From that moment, convinced about their product vision we started iterating, with David as product owner, on what became the REST API which was the backbone of the soon to be built web, Android and iOS apps.
From an extremely agile working scheme and an ongoing expansion of the team working on it, we ended with a very productive scenario, where goals were achieved by sprints and the product was able to launch, in its initial version, in scheduled date and time (September 2013).
After the initial version, new features and product pivots were achieved with a constant iteration with Keith and his dev team..
Due to the product's sensitivity (health), it needed to have high availability, being very tolerant to server failures and ready to scale.
Receive, store and analyse larges amounts of data from sensors and hubs.
The backend was fully built with Python/Django while the frontend was built with AngularJS. We worked with several services of the Amazon stack including EC2, S3, DynamoDB, RDS, ElastiCache. Part of the deployment automation was achieved with Ansible, and other part by switching our stack to use Docker for both production and development.
As a result Lively app became a fully functional platform, which totally gathered $7.3M in venture capital, served thousands of customers and after 2 years in operation was acquired by GreatCall.
We relied on Tryolabs exclusively to build out our web stack, mobile device APIs, and a complex, data analysis oriented backend for wireless sensor networks, all of which were completed with high quality, along expected timelines, and with clear visibility into ongoing status.