Machine learning
development services

Machine learning development services

Machine learning development is the process of designing, building, and deploying ML-enabled software for companies to address their business needs and gain a competitive advantage. Combining industry expertise and the latest IT advancements, Itransition offers comprehensive machine learning development services to create custom ML solutions that automate business processes, drive efficiency, and improve decision-making.

Why Itransition

5+ years of building AI-based solutions

Solid expertise in machine learning, data science, big data, and RPA

Adherence to HIPAA, GDPR, FDA, and other standards and regulations

Standing partnerships with Microsoft and AWS

Client spotlight

AI-powered shoppable video platform

+25%

client satisfaction

Computer vision

We enhanced a video ecommerce platform with machine learning capabilities to enable automated recognition of more than 1.5 million products across images and videos. 

AI-powered platform for a fashion retailer 

+8%

buyer conversion rate 

Computer visionData mining

We built a solution to analyze online user behavior with machine learning and personalize user interactions, increasing the visitor-to-buyer conversion rate.

Telemedicine-ready EHR 

Enhanced

doctor-patient communication 

Natural language processing

We created an EHR solution with innovative voice recognition, smartpen, and clinical text analysis capabilities to optimize medical workflows and product usability.

ML-based solution for brand recognition and reporting

image recognition

We developed a user-friendly ML-based image recognition solution for identifying brands in images and generating bespoke reports.

AI-powered shoppable video platform

+25%

client satisfaction

Computer vision

We enhanced a video ecommerce platform with machine learning capabilities to enable automated recognition of more than 1.5 million products across images and videos. 

AI-powered platform for a fashion retailer 

+8%

buyer conversion rate 

Computer visionData mining

We built a solution to analyze online user behavior with machine learning and personalize user interactions, increasing the visitor-to-buyer conversion rate.

Telemedicine-ready EHR 

Enhanced

doctor-patient communication 

Natural language processing

We created an EHR solution with innovative voice recognition, smartpen, and clinical text analysis capabilities to optimize medical workflows and product usability.

ML-based solution for brand recognition and reporting

image recognition

We developed a user-friendly ML-based image recognition solution for identifying brands in images and generating bespoke reports.

AI-powered shoppable video platform

+25%

client satisfaction

Computer vision

We enhanced a video ecommerce platform with machine learning capabilities to enable automated recognition of more than 1.5 million products across images and videos. 

AI-powered platform for a fashion retailer 

+8%

buyer conversion rate 

Computer visionData mining

We built a solution to analyze online user behavior with machine learning and personalize user interactions, increasing the visitor-to-buyer conversion rate.

Telemedicine-ready EHR 

Enhanced

doctor-patient communication 

Natural language processing

We created an EHR solution with innovative voice recognition, smartpen, and clinical text analysis capabilities to optimize medical workflows and product usability.

ML-based solution for brand recognition and reporting

image recognition

We developed a user-friendly ML-based image recognition solution for identifying brands in images and generating bespoke reports.

Want to entrust your ML project to a reliable technology vendor?

Contact us

Machine learning solutions we build

As a part of our ML consulting service offering, we develop future-proof ML solutions for companies to automate time-consuming activities and assist human employees.

We create machine learning solutions powered by intelligent algorithms that derive meaningful insights from various visual inputs, helping users take proper actions.

Customer tracking

Detect humans and their faces, emotions, and gestures, count people, identify suspicious behavior and theft, analyze customer sentiment.

Visual inspection

Monitor manufacturing equipment, check adherence to safety protocols, and control production quality with defect detection.
Process digital images to identify abnormalities, achieve an improved medical diagnosis, and rate disease progression.

Natural language processing

We develop ML-powered solutions that can process human text or speech to help computers understand natural language the way humans do and perform actions based on the derived insights.

Conversational AI
(chatbots and virtual assistants)

Engage in a larger number of meaningful conversations, ask relevant questions, and respond with appropriate actions or helpful comments.

Sentiment analysis

Conduct text extraction and classification and understand the sentiment and emotion behind the text to measure brand awareness and brand performance and assess customer service efficiency.

Spam detection

Scan emails for specific language, to prevent spam or phishing, and to enhance user experience.

Data mining

We create software with data mining capabilities for companies to aggregate large data volumes and discover correlations, trends, and anomalies. This solution can help identify the probability of a particular business outcome or forecast future events and results.

Identify unexpected events and patterns in data to detect fraud, malicious traffic, production defects, and more to take preventive actions.

Dynamically segment customers and target them with personalized offers, content, and services.

Next-best action

Predict the optimal set of customer-oriented actions, e.g., call customer representative, send a targeted offer, or forward an abandoned cart email, to find new sales opportunities, deliver relevant messages, and prevent churn.

Our machine learning development roadmap

1

Business needs analysis

Business needs elicitation 

Evaluation of the current technology environment

Selection of an optimal ML use case

Functional and non-functional requirements definition

Project scope definition

Basic team composition:
a business solution consultant, an ML solution architect

2

ML solution design

Initial data analysis

Architecture design

Implementation approach and tech stack selection

PoC scope outline (if needed)

Deliverables, timeline, budget, and team establishment

Basic team composition:
a business solution consultant and an ML solution architect

3

ML solution development

Data preparation and validation

Feature engineering and selection 

ML algorithm selection and model training

ML models performance metrics evaluation

Optimal model selection

Basic team composition:
a data/ML engineer, a project manager, a business analyst, and a QA engineer 

4

Integration and deployment

ML solution integration into the existing environment 

ML solution quality assurance 

ML solution deployment to the production environment

ML model scaling in the target environment

On-demand deployment automation with DevOps tool

Basic team composition:
an MLOps engineer, a data/ML engineer, a project manager, and a QA engineer

5

Support

Maintenance of the production environment

ML solution performance monitoring

Improvement of solution accuracy/performance 

Resolving edge cases

User training and support provision

Basic team composition:
a support engineer and a project manager

Technologies we work with

  • Python
  • R
  • C++
  • Java/Kotlin

  • TensorFlow Keras PyTorch
  • Skikit-Learn Theano MXNet
  • NumPy NLTK Pandas
  • SparkML Sonnet
  • DarkNet Catboost
  • XGBoost Annoy
  • Faiss NvidiaDigits

  • Residual neural network (ResNet) Recurrent neural network (RNN) Convolutional neural network (CNN) Regression models Categorization models
  • Generative adversarial network (GAN) Neural radiance field (NeRF) Clustering algorithms YoloNet AlphaPose
  • Skeleton detection Pose2Seg RetinaFace U-Net DBSCAN

  • Amazon SageMaker Amazon Rekognition Amazon Lex Amazon Polly
  • Azure Machine Learning Azure Cognitive Services Language Understanding Intelligent Service Azure Bot Services
  • Cloud Machine Learning Engine Cloud Vision API Cloud Natural Language AI Cloud Speech API DialogFlow

  • BI Tools
  • Power BI
  • Tableau
  • Qlik
  • Custom visualization
  • Plotly
  • Matplotlib
  • ggplot2
  • Highcharts

ML development across industries

We develop ML solutions that help capture product demand and market trends, manage risks and customer churn, and tailor advertising, pricing, products, and services according to customers’ needs and demands. 

Retail

We build ML-powered solutions that help personalize customer interactions in real-time with tailored recommendations, advanced search engines, and chatbots for 24/7 customer support. We can also create fraud and anomaly detection solutions to secure your online store. 

Ecommerce

We deliver ML capabilities to healthcare organizations to help improve the quality of medical diagnosis, patient experience, and disease treatment. Our experts can develop medical image analysis, visual assistants, chatbots, and virtual nursing with speech recognition solutions.

Healthcare

We engineer solutions to help financial professionals automate back-office operations, facilitate fraud detection, enhance customer support, and accurately measure credit risks. Itransition’s developers can deliver virtual assistants and chatbots, personalized service offerings, customer credit profiles assessment, and predictive modeling.

Banking

We develop custom machine learning systems that deliver personalized learning experiences through tailored content recommendations and learning plans, adaptive training activities, dynamic adjustments of learning speed and curricula.

Education

Itransition’s machine learning developers create ML-enabled solutions that predict stock prices, forecast market trends and track financial instruments’ performance, detect fraud, and send customizable alerts.

Stock market

We create tailored machine learning applications that help companies dynamically segment customers, forecast demand, personalize ads, drive contextual advertising, and enhance customer engagement, retention and loyalty. 

Marketing

Our machine learning engineers develop solutions to help real estate companies stay profitable by making accurate market value and claim cost predictions, automating property performance monitoring, and enhancing customer experience with personalized recommendations and virtual tours.

Real estate

Itransition creates ML solutions for manufacturers to optimize production processes and improve their efficiency with augmented quality controls, digital twins, predictive maintenance, and accurate product demand forecasting.

Manufacturing

Itransition’s machine learning engineers build machine learning applications to help logistics companies optimize routes, boost fleet productivity, enhance traffic management, and ensure better passenger and cargo safety. We can deliver logistics-specific solutions for accurate delay predictions, driver assistance, traffic monitoring, and predictive maintenance.

Logistics

Our machine learning developers engineer robust solutions for the agriculture sector to improve crop performance and food safety by automatically detecting diseases and crop quality, monitoring livestock health, and generating personalized treatment and management recommendations.

Agriculture

Learn about other industry solutions from our consultants

Contact us

Benefits of machine learning development

Outstanding customer experience

Provided by ML-powered chatbots, virtual assistants, recommendation engines, and marketing automation tools.

Increased operational efficiency

Due to automation of repetitive and time-consuming activities, timely delivery of valuable analytics insights, accurate risk forecasting, and bottlenecks recognition.

Production efficiency

Enabled by accurate predictions of market trends and customer behavior tendencies, as well as demand and throughput forecasting.

Increased useful life of assets

Due to accurate calculation of asset remaining lifetime, predictive maintenance, automated asset maintenance, and upgrade planning.

Error reduction

Owing to the elimination of the human factor as a result of machine learning algorithms implementation.

Related services

Data science

Data science

Itransition offers data science services to enable companies to elicit insights from voluminous noisy data with the help of advanced algorithms and methods and resolve the most deliberate business problems.

Artificial intelligence

We help companies design and implement AI-enabled solutions to drive automation, personalize customer interactions, improve product quality, mitigate risks, and elevate employees’ capabilities and performance.

Predictive analytics

We create innovative business intelligence and analytics solutions to help enterprises discover data patterns and trends and forecast market trends, financial risks, customer behavior changes, and product demand.

Big data

Itransition builds solutions to help organizations capture and process big data and derive insights to optimize business processes and gain a competitive advantage.

RPA

We deliver ML-powered solutions that assist or substitute employees in routine tasks and increase results’ accuracy, decrease operational costs, and improve employees’ productivity and satisfaction.

Want to embrace ML capabilities?

Contact us

ML development FAQs

How much does machine learning software cost?

There are numerous real-world ML use cases, ranging from a simple chatbot to a complex ML solution with sophisticated logic behind it. Thus, the prices vary greatly. When estimating ML TCO, we factor in data-related attributes (number of data sources, data type, data volume, and data quality used for ML development), ML accuracy requirements, ML approach and methodology, and infrastructure costs. Basic PoC implementation starts from $10,000. If you want to get a ballpark estimation of the cost and resources needed to implement your ML project, contact our consultants.

How much data and what type of data is needed for a solution? What if we don’t have enough?

Machine learning models are trained on labeled data (in supervised machine learning) and unlabeled data (in unsupervised machine learning), so you can use any training data that can be converted into numbers, including tabular data, text, images, video, graphs, etc.   Concerning data volume, the rule of thumb is: the more data the better. What is more, data should also be as close as possible to production data. At the same time, data diversity is as important as data volume. In case data volume or quality is not satisfactory, we help you collect new data sets or reuse available training sets.

What pricing models do you offer?

At Itransition, we offer two pricing models for delivering machine learning projects:

  • Time and material
    Provision of ML development experts for projects with changing requirements due to scope uncertainty/expansion, where a customer pays based on the number of person-hours and materials spent to perform the required work.
  • Fixed-price
    Provision of ML development experts for the projects with approved and fixed scope, development budget, and timeline for a fixed price.   

Do we need to pay for the infrastructure to train the ML model?

No, we handle ML model development and train it on our instances.
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