Here's an overview of our technology stack and links to some case-studies, for example "how we optimised our API to reduce network overhead by 70% using Protocol Buffers".

Stacks


Frontend Web

Language, Framework and Tools

3rd Party Services

Backend

Languages

  • Go

AWS Technologies

  • Batch

  • DynamoDB

  • EKS

  • Lambda

  • S3

  • SQS

  • Step Functions

  • (And many more...)

3rd Party Tools


Product Design

Tools


Data Science

Languages

  • Python

  • SQL

Technologies

  • Flask

  • Jupyter

  • Matplotlib

  • Numpy

  • Pandas

  • Scikit-learn

  • Scipy

  • Tensorflow 2 + tf.keras

  • XGBoost

AWS Services

 Infrastructure


Android

 Languages

  • Kotlin

  • Java (legacy only)

Google Technologies

  • Google Vision

  • Jetpack Compose

  • MLKit

  • Architecture components (LiveData, ViewModel)

  • Firebase: Messaging, A|B Testing, ML

  • Google Pay

  • Material Design

  • Testing Frameworks: JUnit, MockK, Mockito / DaggerMock

  • WorkManager

3rd Party Tools / Dependencies


iOS

 Languages & Architecture

  • Swift

  • MVVM + Coordinators

Apple Technologies

  • Accelerate

  • Apple Pay

  • AVKit

  • Combine

  • Compositional Layouts

  • CoreAnimation

  • CoreData

  • CoreGraphics

  • CoreImage

  • CoreML

  • Diffable DataSource

  • Grand Central Dispatch

  • Metal

  • Operations

  • PassKit

  • Photos

  • Swift Package Manager

  • UIKit

  • UserNotifications

  • Vision

  • XCTest

  • Xcode Cloud

 3rd Party Tools / Dependencies


DevOps

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