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Enabling machines and humans to transform vision into insight.

Our mission is to teach computers how to describe and understand what they see.

Available on:

Industry:

Software & Services

Services:

Web Development
Product Ownership
UX/UI Design
DevOps

The Problem

An oportunity for Machine Learning as a Service product that connects the bridges between ML and SaaS.

The Solution

Delivered a production-grade visual machine learning SaaS product, with monitoring and logging functionalities and continue the development adding more features to it.

The Result

A fully functional machine learning product. Main features includes identify individuals from sources, compare individuals to see if they are the same person from sources. The sources can be photos, videos or even live stream from cameras.

Technologies we used:

ReactJs

ReactJs is in top 3 client-side frameworks, its main competitive advantages are the versatility and the extensibility of the framework.

Java Spring

Spring is THE server-side framework for Java and the best choice for a scalable, modular and blazing-fast application.

Gitlab CI/CD Pipelines

GitLab CI/CD Pipelines is a tool that automates steps in the SDLC like builds, tests, and deployments.

Docker

Docker is one of the pillars for a scalable and HA startup.
Using Docker is a standard for delivering quality services every time.

Solr

Solr is an open-source enterprise-search platform, written in Java, from the Apache Lucene project. Its major features include full-text search, hit highlighting, faceted search, real-time indexing, dynamic clustering, database integration, NoSQL features and rich document handling.

Minio

MinIO is a cloud storage server compatible with Amazon S3, released under Apache License v2. As an object store, MinIO can store unstructured data such as photos, videos, log files, backups and container images.

SocketIO

Socket.IO is a JavaScript library for realtime web applications. It enables realtime, bi-directional communication between web clients and servers.

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