ML services and solutions from certified machine learning experts
The business value of machine learning
of total profit by 2030 will come from AI-powered product enhancements
PwC
expected cost reduction in the next 3 years among intelligent automation adopters
Deloitte
faster response time is expected by 2024 from companies adopting AI
Oracle
Itransition at a glance
5+ years of experience delivering successful ML projects
Proven expertise in artificial intelligence, machine learning, deep learning, and data science
25+ years in IT consulting and software development services
Adherence to HIPAA, GDPR, FDA, and other standards and regulations
Standing partnerships with Microsoft and AWS
Client spotlight
+25%
client satisfaction
AI-powered shoppable video platform
We deployed ML and computer vision into a video ecommerce platform to enable automated recognition of more than 1.5 million products across images and videos.
Enhanced
doctor-patient communication
Telemedicine-ready EHR
We developed an EHR solution with innovative voice recognition, smartpen, and clinical text analysis to optimize medical workflows and enhance product usability.
+8%
buyer conversion rate
AI-powered platform for a fashion retailer
We created a solution to conduct online user behavior analysis with ML to personalize user interactions and increase the visitors-to-buyers conversion rate.
+25%
client satisfaction
AI-powered shoppable video platform
We deployed ML and computer vision into a video ecommerce platform to enable automated recognition of more than 1.5 million products across images and videos.
Enhanced
doctor-patient communication
Telemedicine-ready EHR
We developed an EHR solution with innovative voice recognition, smartpen, and clinical text analysis to optimize medical workflows and enhance product usability.
+8%
buyer conversion rate
AI-powered platform for a fashion retailer
We created a solution to conduct online user behavior analysis with ML to personalize user interactions and increase the visitors-to-buyers conversion rate.
+25%
client satisfaction
AI-powered shoppable video platform
We deployed ML and computer vision into a video ecommerce platform to enable automated recognition of more than 1.5 million products across images and videos.
Enhanced
doctor-patient communication
Telemedicine-ready EHR
We developed an EHR solution with innovative voice recognition, smartpen, and clinical text analysis to optimize medical workflows and enhance product usability.
+8%
buyer conversion rate
AI-powered platform for a fashion retailer
We created a solution to conduct online user behavior analysis with ML to personalize user interactions and increase the visitors-to-buyers conversion rate.
Our customers say
Over the course of our collaboration with Itransition, we were consistently impressed with both skill and dedication their team employed to fulfill our business needs. Itransition’s involvement extended beyond the technical realization of the project, they acted as consultants, continuously helping us hone the project vision and suggesting approaches that would be best suited for the intricacies of our business.
Looking for top machine learning experts for your project?
Our machine learning services
Our AI researchers and data scientists offer end-to-end assistance for organizations that implement machine learning solutions or upgrade existing machine learning applications. Our services range from business needs analysis and designing ML models to selecting the optimal strategy and technologies for implementing ML.
We develop scale-ready MVPs and enterprise-wide ML tools to help our clients solve business problems and gain an advantage over their competitors. Our services include ML requirements elicitation, data management and visualization, machine learning model development and tuning, integration, and maintenance.
Our service delivery pipeline
1
Business needs analysis
We hold discovery workshops, interviews, and process observations to elicit business needs and user expectations, and assess the client’s technical environment. Based on the results, we select the suitable ML use case and define the ML solution’s scope and functional and non-functional requirements.
Basic team composition:
- A business solution consultant
- An ML solution architect
2
Initial data analysis
We carry out an exploratory analysis of the available data sources, both owned by the customer and from public databases, required to implement the project. After that, we conduct data cleansing, assist with data imputation or dimension reduction, design a data pre-processing pipeline, and guide data analysis flow creation.
Basic team composition:
- An ML solution architect
- A data scientist/ML engineer
3
ML solution design
In line with the elicited business needs, we design the architecture of the ML solution, define an implementation strategy, suggest optimal AI techniques, machine learning algorithms, and draw up a tech stack that can include both open-source and licensed software. If we need to deliver a PoC, we also outline its scope and optimal approach. Additionally, we define the timeline and budget for the project.
Basic team composition:
- A business solution consultant
- An ML solution architect
4
Building the ML solution
Our software engineers perform data pre-processing, including data cleansing, annotation and transformation. Then the team defines ML solution evaluation criteria and trains the model with supervised, unsupervised and reinforcement approaches. To achieve the desired output, our programmers can build an ensemble of models while ensuring ML solution’s security and compliance.
Basic team composition:
- A data/machine learning engineer
- A project manager
- A business analyst
- A QA engineer
5
Integration and deployment
We identify a suitable deployment environment and create the strategy to integrate the ML solution into the business software and go live. After we make sure the ML solution adheres to testing guidelines, we deploy it to the production environment and ensure the ML model’s scalability, proper performance, and security.
Basic team composition:
- An MLOps
- A data/ML engineer
- A project manager
- A QA engineer
6
ML support
We monitor the model's performance and can improve the accuracy of ML output by retraining the solution using new data from the production environment with the customer’s approval, all without interrupting the solution’s operation. We also conduct user training and support, create tutorials, and an optimization strategy on request.
Basic team composition:
- A support engineer
- A project manager
Machine learning solutions across industries
Retail
- Predicting product demand and retail trends
- Targeted advertising, dynamic pricing, and promotions tailored to customers’ needs
- Anticipatory shipping and smart route planning
- Anomaly detection and intelligent video surveillance
Ecommerce
- Advanced recommendation and search engines
- Chatbots for improving customer experience
- Contextual shopping features
- Demand forecasting
- Fraud and anomaly detection for safer purchasing experience
Healthcare
- Diagnostics and identification of high-risk patients
- Consulting chatbots and virtual assistants
- Drug discovery and development
- Automated EHR processes and virtual nursing
Banking
- Personalized service offerings
- Automated back-office operations and NLP capabilities
- Fraud detection
- Virtual assistants for customer support
- Customers’ credit profiles assessment
Education
- Tailored content recommendations and customized learning paths
- Adaptive training activities for personalized learning experiences
- Dynamic adjustment of learning speed and personal curricula
- Bots to automate and streamline manual processes
- NLP-based real-time translation and transcription of eLearning content
Stock market
- Stock price prediction
- Trade execution and market making algorithms
- Stock market forecasting engines and autonomous stock trackers
- Automated fraud detection and customizable alert systems for managing risk
Marketing
- Automated customer segmentation and new customer segments discovery
- Ad personalization and contextual advertising
- Marketing automation
- NLP capabilities for enhanced customer interactions
Real estate
- Recommendation engines and virtual tours
- Market value prediction
- Automated property management
- Property performance monitoring and price prediction
Manufacturing
- Predictive maintenance to maximize asset lifetime
- RPA and digital twins for production efficiency improvement
- Augmented quality control to timely identify anomalies
- Product demand forecasting
Logistics
- Dynamic supply and demand balancing for a resilient supply chain
- Estimated time of arrival (ETA) and warehouse workloads prediction
- Dynamic route optimization for timely delivery of goods
Agriculture
- Automated disease detection and treatment recommendations
- Yield mapping and estimation
- Crop quality detection and classification
- Livestock health aspects monitoring
We can do more
Hire machine learning experts from Itransition
Machine learning solutions for real-world use cases
Computer vision
Building solutions that enable computers to process, analyze, and make sense out of visual data - images and videos - to trigger an action or a set of actions.
Customer tracking
Itransition’s team creates solutions that process video streams in real time to detect humans, count them, analyze customer behavior within a store, detect suspicious behavior, etc.
Quality control
We help implement automated visual quality control of production processes and assembly lines to eliminate error-prone manual inspection processes, increase speed and accuracy, and facilitate objectiveness and scalability.
We create solutions for scanning X-rays, computed tomography scans, ultrasound, mammograms, and magnetic resonance imaging to identify abnormalities not visible to the human eye, make a diagnosis, rate disease progression and treatment response.
Natural language processing
We build smart ML-powered solutions to interpret and extract meaning from written and oral natural language.
Chatbots
We help businesses streamline customer services with chatbots that assist customers and answer their questions 24/7, making customer journeys smoother and freeing up support agents’ time.
Sentiment analysis
We develop ML-powered solutions to help organizations get valuable insights from voluminous customer data and chatbots and use them to optimize their products and services or improve customer experience.
TTS/STT conversion
We create ML-enabled solutions that automatically recognize speech and convert it into text and vice versa for virtual assistants and chatbots, voice typing and commanding, call center transcription, medical record analysis, voice translation, and more.
Data mining
Itransition’s team creates solutions using deep neural networks such as artificial neural networks and recurrent neural networks that are able to aggregate voluminous data sets to derive business value out of them and solve non-trivial problems.
Itransition’s machine learning experts deliver custom recommender systems that automatically process data output generated by customers to segment them based on the pre-defined criteria and target them with personalized content, including product recommendations and alternatives and personalized merchandise.
Itransition develops ML-based solutions that are trained to predict potential dangers (fraudulent transactions, machine breakdown, patient condition deterioration) and help organizations prevent them.
Our team delivers ML-powered software to timely detect suspicious behavioral patterns that could be clues to fraud like money laundering, market manipulation, as well as tax and insurance fraud.
Predictive maintenance
Our machine learning experts create solutions enabling condition-based maintenance for companies, reducing equipment downtime and expenses, increasing asset lifetime, and improving overall operational efficiency.
Related services
Data science
A full range of data science services to help you derive valuable insights from business data and use them to address the most pressing business challenges.
Artificial intelligence
AI solutions and services to help businesses drive automation across the enterprise, improve product and service quality, enhance customer experience, and solve non-trivial business problems with advanced technology.
Predictive analytics
ML-powered analytics solutions for predicting and identifying market trends, forecasting risks, predicting customer behavior and product demand, and automating decision-making.
Big data
Big data solutions to collect and use large volumes of multi-structured data to help businesses find hidden patterns, drill down into the root causes of problems, and better understand customers.
RPA
ML solutions that assist or substitute employees in routine and demanding activities to drive accuracy and productivity, cut operational costs, and better allocate human resources.
Have ideas about your future ML solution?
Machine learning technologies we use
- Python
- R
- C++
- Java/Kotlin
- TensorFlow
- Skikit-Learn
- NumPy
- SparkML
- DarkNet
- XGBoost
- Faiss
- Keras
- Theano
- NLTK
- Sonnet
- Catboost
- Annoy
- NvidiaDigits
- PyTorch
- MXNet
- Pandas
- Residual neural network (ResNet)
- Categorization models
- YoloNet
- RetinaFace
- Recurrent neural network (RNN)
- Generative adversarial network (GAN)
- AlphaPose
- U-Net
- Convolutional neural network (CNN)
- Neural radiance field (NeRF)
- Skeleton detection
- DBSCAN
- Regression models
- Clustering algorithms
- Pose2Seg
- Amazon SageMaker
- Azure Machine Learning
- Cloud Machine Learning Engine
- Amazon Rekognition
- Azure Cognitive Services
- Cloud Vision API
- Amazon Lex
- Language Understanding Intelligent Service
- Cloud Natural Language AI
- Amazon Polly
- Azure Bot Services
- Cloud Speech API
- DialogFlow
Machine learning FAQs
What can machine learning do for my business?
ML implementation brings numerous benefits, the most significant being cost reduction due to the automation of repetitive manual tasks and an increase in operational efficiency due to augmenting human intelligence.
How do we start with machine learning?
Every project in the field of machine learning begins with a careful analysis of the company’s business needs, identification of the optimal technology solution, and the delivery of PoC if verification of the chosen approach/methodology is required.
How much does a machine learning solution cost?
To define the TCO of an ML solution, you should 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
- ML implementation and maintenance costs
- Infrastructure costs
- Software licensing
Basic ML PoC implementation starts from $10,000. If you need a ballpark estimation of your ML project, contact our consultants.
What pricing models do you offer?
For machine learning projects, we usually offer time and material and fixed-price pricing models.
What are the major challenges of implementing ML models?
The major challenge of implementing an ML solution is ensuring the proper quality of the ML output.
Do we need to pay for the infrastructure to train the ML model?
No, we train the ML models on our instances, you’ll need the infrastructure only for rolling out the solution post-development.
Insights
Using AI to scale wealth management
Discover how wealth management companies use AI to generate more leads, automate back-office tasks, improve customer relationships, and improve bottom lines
Insights
Computer vision in retail: top 5 applications
We look into the most prominent use cases of computer vision in retail used by leading vendors to create personalized and convenient experience in their stores.
Insights
Video object recognition and detection
Get to know the capabilities of video object recognition and detection technologies, as well as the range of FOSS and commercial tools available.
Insights
AI in the automotive industry: use cases, success stories & adoption guidelines
Explore key use cases, payoffs, and real-life examples of AI in the automotive industry, along with adoption challenges and tips to address them.
Insights
Cognitive automation: augmenting bots with intelligence
Learn how RPA and AI can work together to achieve superior business efficiency within the framework of cognitive automation.
Case study
Custom ML algorithms for an insurance platform
We developed and trained an AI model that predicts insurance application conversion, helping the customer select targeted user price policies and discounts.
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