MobileForge

MobileForge is a deployable device intelligence platform, that ensures all data collected from user's mobile devices can be securely transmitted to the institution's infrastructure, where profiling and processing take place — maintaining full control and compliance within institutional premises.

Key Features

• Modular architecture
• Scalable deployment options
• Robust data syncing with minimal drops
• Powerful data features and insights for user profiling
• Utilizes open-source databases (MongoDB and PostgreSQL) for efficient and reliable data storage

Explore the sections below to learn more about MobileForge's components, deployment strategies, scaling guidelines, and data schemas.

Architecture Overview

The diagram below illustrates a typical deployment of the MobileForge platform. It is intended as a reference architecture showcasing how various components work together in a production-grade setup.

This architecture highlights key components such as -

1. Data ingestion from mobile devices
2. Secure transmission to institutional infrastructure
3. Robust data syncing
4. The combined use of MongoDB and PostgreSQL for optimized storage and profiling operations

Data Privacy

The MobileForge platform maintains strict data privacy by design. Only authentication keys and API usage metrics are transmitted to Credeau servers for billing and compliance purposes. All user data remains within your institution's infrastructure, ensuring complete data sovereignty and privacy.

Components

The MobileForge solution can be broken down into 2 major pipelines, where each is composed of modular services that can be independently scaled and deployed.

1. Data Sync

Responsible for securely ingesting data from mobile devices and storing it for downstream processing.

Services -

• Producer API: Acts as an entry point to the system, receiving data from the SDK.

• Kafka Stream: Serves as the backbone for streaming data reliably between services.

• Data Consumers: Process incoming data from Kafka and store into the databases. These can be grouped basis the type of data source to consume.

• Databases:

  • MongoDB: Used for storing the raw data collected from users' devices.
  • PostgreSQL: Used for storing user metadata and API usage data.

2. Insights Generation

Provides APIs for reading, profiling, and deriving insights from the synced data.

Services -

• Insights API: Delivers processed insights by executing in-house algorithms and machine learning models on top of user's synced data.

• Extraction API: Extracts relevant financial signals from user's raw data.

• Databases:

  • MongoDB: Used for fetching the raw data collected from users' devices.
  • PostgreSQL: Used for fetching user metadata and storing derived insights from the raw data.