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AI & Machine Learning Development Services

We use machine learning methods to create smart solutions that solve business problems.
What we do What’s included?

What we do

Integra Sources provides AI and machine learning software development services for companies and individuals looking to leverage machine learning techniques and algorithms for predictions, anomaly detections, automation, and other applications. Our team specializes in AI technologies and computer vision systems for IoT projects and embedded systems. We provide custom machine learning development and tailor ML-based apps for your particular business needs.

What's included?

Within the scope of artificial intelligence development services, we work on a wide variety of problems including big data processing, image recognition, video analysis, object detection, and tracking, face recognition, and emotion recognition to name a few. The global artificial intelligence and machine learning market is constantly growing and covering new industries and areas of application.

As a machine learning development company, we build custom machine learning and AI-based software solutions for healthcare, manufacturing, and other industries. To deliver intelligent systems, we design algorithms that can learn from data and make predictions.





Check out our recent case study

Machine learning OCR Computer vision Mobile app development

Optical Character Recognition Module for Invoice Capture Software

The OCR module makes it possible to extract information including the invoice date, number, the total sum of the purchase, and line-items.

Our clients include enterprise companies, research centers, and innovative startups from all over the world

How we work

Check out the table below to learn more about how we work and where your involvement is most needed depending on the type of collaboration model:

AREA OF RESPONSIBILITY

PROJECT-BASED OUTSOURCING

DEDICATED DEVELOPMENT TEAM

RESEARCH & DEVELOPMENT

PROJECT REQUIREMENTS

YOU

SHARED

YOU

UI DESIGN

SHARED

SHARED

SHARED

SOFTWARE ARCHITECTURE

INTEGRA

INTEGRA

INTEGRA

DATA ANALYTICS

INTEGRA

SHARED

SHARED

DEVELOPMENT

INTEGRA

INTEGRA

INTEGRA

TESTING

INTEGRA

SHARED

SHARED

DELIVERY MANAGEMENT

SHARED

SHARED

Frequently Asked Questions

Read this information to better understand the process of AI and machine learning development.

What’s the difference between artificial intelligence, deep learning, and machine learning?

In a nutshell, artificial intelligence is a way to make machines think like humans, and machine learning is an approach to achieve artificial intelligence. Machine learning development is about writing algorithms that can make sense of data – classify data, find patterns and correlations, and learn from data to make predictions – all without human intervention. Deep learning in its turn is one of the most widely used techniques for implementing machine learning. It uses neural network architecture that consists of multiple layers to learn features from the data.

 

Within our machine learning development services, our firm delivers projects of various complexity from a simple ML-based application to a complex AI-enabled system.

 

To build a successful deep learning application, we need a large amount of data to train the model and a powerful data processing system.

What technologies do you use to build machine learning systems?

For projects with advanced image processing needs, we use OpenCV library. We also use Amazon and Azure's Machine Learning services to build predictive models and automate data processing tasks. Other machine learning technologies in our tech stack include TensorFlow, Keras, Caffe/Caffe2, and OpenALPR.

What tasks can you solve with ML?

Machine learning tasks we’re best at include:

  • Training neural networks to build classifications
  • Object recognition
  • OCR
  • Face recognition
  • Human detection
  • Predictive analytics
  • Natural Language Processing (NLP) for text and voice applications
  • Recommender systems

What does the machine learning development process look like?

We normally use a standard workflow for machine learning solutions development. First, we need to look at your problem and see if machine learning is the best method to solve it. If yes, then the next step is to collect meaningful data for training purposes. We will classify and analyze these data, and when our dataset is ready, we can start a learning model development. One of the most important stages in this process is training the model on the existing dataset. This usually takes a few design experiments and iterations. Once we get the proof of concept, we’ll integrate our model with your solution and launch it to production.

What if I don’t have enough data?

Not enough data will lead to unsatisfying results. The more data the more accurate the algorithm. If you don’t have the amount of data, we need to build a training model, we will try to collect them from online sources if possible. There are a lot of open source resources that contain databases with categorized data that we can use to train our system. Also, there are some paid resources where we can create a database with the needed information for training purposes.

Where is AI development mostly applied?

Artificial intelligence has a really broad range of applications. It is widely used in computer science, aviation, marketing, telecommunications, and logistics. AI is applied for healthcare, educational, financial, and military projects and in many other fields.

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