DeepStack - World first self-managed AI Server

The field of Artificial Intelligence has progressed incredibly with the emergence of powerful algorithms like Deep Learning, High Performance hardware like the NVIDIA GPUs as well the massive amount of textual, image,sound and numerical data generated on the internet and embedded devices. This progress has led tremendous possibilities in Computer VisionNatural Language processingSpeech and Data Analytics.

Like every other technological transformation, today’s modern AI started at a very low-abstract level in which only a few with the technical expertise as well as the resources can actually harness its potentials and deploy in an applicable use case. Today, most application of modern AI is done by companies and government agencies with the finance to hire the few available experts that can build an entire AI solution stack.

To fix the technical challenges faced in deploying modern AI, a number of cognitive cloud services emerged and started offering AI resources via APIson a pay-as-you-use basis. As convenient as these services may be when compared with the task of setting up the entire AI solution stack in-house, there are a number of strings attached to these cognitive cloud solutions; a number of them are:

  • High Cost: It is expensive to deploy in real-time and long-term basis use cases, considering API costs and bandwidth costs when large-sized input data like images and videos are involved
  • Network Dependency: There is need to maintain a constant supply of reliable connection to the internet which means places with little or no internet resources are alienated from these solutions.
  • Privacy: Every single input data generated will have to be sent to third party servers irrespective of the confidentiality of the data.

At DeepQuest AIwe recognize the impact today’s state-of-the-art AI will have on every field of study and practice. We decided to built an ultimate AIsolution that will ensure you can easily setup, integrate and deploy state-of-the-art AI resources in-house. Therefore, we started building DeepStack.

DeepStack is a dockerized AI server that provides all the simplicity cognitive cloud services provides through the use of API endpoints but with the fact that it can installed on your own computer system or private cloud-based virtual machine and it works completely offline and without connecting to a third party server. In short, DeepStack once installed and running on your computer system will provide a central AI engine with an IP address like that you can send data to it via endpoints like /detection, /face, /scene from any computer, smartphone or IoT device within a Local Area Network (e.g Wifi). This ensures the AI Server can work with any software and application built with most programming languages like NodeJS, Python, Java, Ruby, PHP, C# and more.

The first version of DeepStack will be available for Insider Preview Program where a few selected individuals will get a copy of DeepStack for free with one-on-one support provided along with sample codes, sample client applications and their source code, documentations and more via a dedicated slack group. These version will support a number of computer vision features such as object detection, face detection, scene recognition, action recognition and more.

We are inviting you to be part of the DeepStack Insider Preview Program.We are running a developer survey which serves as the sign up form for the insider program to get feedback that will give us the insight to tailor the features that are to be built into DeepStack. Click this link to take the survey sign up for the insider program.

At DeepQuest AI, Our Mission which we choose to accept is to advance and democratize Artificial Intelligence and make it accessible to every individual and corporate entity of all sizes on the planet.

Visit our website via to learn more about our open source projects, tutorials, free machine learning and deep learning e-book, datasets and solutions.

Published by

Moses Olafenwa

A Machine Learning, Deep Learning and Computer Vision Developer and Researcher. Created and maintains ImageAI, a Python library for deep learning and computer vision tasks with 50,000+ users in 55+ countries.