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Recommendo

Reactive Product Development

Headquarters

Austin, Texas, USA

Industry

Internet

Technology Used

Scala, Apache Spark, Lift Framework, Angular.js, Akka, MongoDB, Spray, iOS, Android

Recommendo is a leading Recommendation Network designed to get and send recommendations to friends. It is used to share discoveries and ask friends for one-to-one advice on various matters. The system’s strength is the quality of the recommendations that travel through the system. The quality of the recommendations makes it a platform of choice for companies who would like to spread sincere recommendations than just stranger ratings.

Challenges

Recommendo required a solution that would be resilient, scalable, and responsive. They also needed a team of experienced developers to build the product ground up

Solutions

Knoldus worked with Recommendo first to create a roadmap leading to the MVP, which could be showcased to the investors and the beta community.

Results

Recommendo was able to get the MVP out to the market on time and attract investors to the product, which has since been launched in the German market to a great response.

Challenges

To increase scalability and developer velocity, Recommendo decided to adopt the Typesafe Reactive Platform along with Lift Framework, thus providing them with the power and security they required. With extreme scalability requirements and extreme responsiveness required, Recommendo required a solution that would be resilient, scalable, and responsive. They also needed a team of experienced developers to build the product ground up who would not only develop the product but would also participate in the business discussions to make the product successful.

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Solution

Knoldus worked with Recommendo first to create a roadmap leading to the MVP (Minimal Viable Product), which could be showcased to the investors and the beta community. Knoldus then worked with Recommendo daily to build the product, always keeping the non-functional and quality aspects as a part of every delivered sprint. The architecture was based on the Reactive Manifesto and was designed to be asynchronous and non-blocking at every level. The data crunching for analyzing big data and machine learning was done with Apache Spark. The presentation layer was built on Angular.js, which talked to the services which are federated for scalability. These services are also consumed by mobile applications. A Lift actor to Akka bridge was built to distribute the product across nodes.

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Results

Recommendo was able to get the MVP out to the market on time and attract investors to the product, which has since been launched in the German market to a great response. The product has evolved a lot based on the market needs, and Knoldus continues to be the engineering team for Recommendo for the next phase of the product.

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