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We are developing the best technology in the world for private debt investments
  • Future Focused – Cloud Native/ Saas/ Microservice Event-Driven Architecture
  • Team – Fully Agile/Flexile/Remote teams
  • Building – Secure Kubernetes Supported Environment where devs can enjoy building great products.
Git Commits
11K+
Completed tasks
4K+
Codelines
1,1Mn+
Slack messages
380K+
Coding languages
12

Our tech stack is a constant
evolutionary machine

  • Flexible Architecture

    Our distributed systems internally exchange a lot of data through, following an Event Driven Architecture.

    Components

    RabbitMQ and Celery for Asynchronous Tasks

    Kafka for Event Streaming

    Redis as a cache Engine of Choice.

  • +40% saved dev. Time 99.9% Uptime

    Our applications run in the AWS Cloud, in a fault tolerant multi-zone setup.

    Components

    Kubernetes for Orchestration

    Jenkins for Pipeline Management

    Vault Hashicorp for Secrets Management

    Git for Version Control

    Prometheus for Real Time Logs

    Grafana for Real Time Monitoring

  • 5+ apps

    Our frontend apps are built with a variety of languages and frameworks on mostly based on Typescript and JavaScript

    Components

    React-JS for rendering visual components

    Redux-JS for managing state and data

    + 35 libraries and npm packages

  • 10+ apps

    We use a variety of backend technologies mostly focused on Python and C# languages.

    Components

    Django Framework for our Macroservices.

    FastAPI Framework for our ML Pipeline

    Flask Framework for our Microservices

    Pandas for Data Manipulation

    Faust Streaming as Kafka Connector

    .NET Core 5 for our Macroservices

    + 45 other python libraries and packages

    + 15 other C# libraries and packages.

  • At peak 5gb/s throughput

    Our distributed systems internally exchange a lot of data through, following an Event Driven Architecture.

    Components

    RabbitMQ and Celery for Asynchronous Tasks

    Kafka for Event Streaming

    Redis as a cache Engine of Choice.

  • 2Tb+ Data Points

    We use AWS Managed Services to handle data and files

    We use

    Aurora Postgres as a Data Storage Solution

    AWS S3 as a file storage solution

    Timescale for managing time-series data

  • 4 models running + 5 under testing

    Our ML Modelling mostly relies on Python and R.

    Libraries that we use

    Pandas for Data Processing

    Vaex for Big Data Processing

    MLFlow for Model Lifecycle Management

With CARDO
Before
Before Cardo
With Cardo
Before Cardo
With Cardo
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Our Offices
  • Milan:
    Via Monte di Pietà 1A, Milan, Italy
  • London:
    40 New Bond St, London W1S 2DE, UK
  • Tirana:
    Office 1: Rruga Adem Jashari 1, Tirana, AL
    Office 2: Blvd Zogu I, Tirana, AL

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