Machine learning consulting
Why choose Itransition
25+ years in IT consulting and software development services
5+ years of experience in machine learning consulting and development
Standing partnerships with Microsoft and AWS
Delivering AI solutions in full adherence to HIPPA, GDPR, FDA, and other standards and regulations
Client spotlight
8%
buyer conversion rate
ML-powered BI platform
Itransition delivered an advanced BI platform with an ML-powered recommender system and computer vision capabilities to help the customer predict user behavior and personalize customer interactions.
25%
customer satisfaction
ML-based shoppable video platform
Our team enhanced a video ecommerce platform with ML-based functionalities, allowing the customer to create shoppable images and videos for online channels and provide a frictionless ecommerce experience.
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.
The scope of our machine learning consulting services
Business analysis
- Identifying business needs via discovery workshops, interviews, and process observations
- Selecting use cases where it makes sense to opt for ML over conventional software
- Assessing the customer’s current technical environment
- Helping define the solution’s functional and non-functional requirements
Initial data analysis
- Defining dataset requirements
- Assisting with data sources selection
- Assessing the quality of available data
- Advising on data analysis and cleaning
- Assisting with data imputation or dimension reduction
- Designing a data preprocessing pipeline
- Offering guidance on the creation of a data analysis flow
Product design
- Suggesting suitable machine learning techniques and ML algorithms
- Helping select a technology stack
- Detailing the ML solution’s architecture
- Advising on UX/UI design
- Planning the development stages (PoC, MVP, and main releases)
- Developing testing strategies
- Advising on ML model performance assessment
- Defining the project's goals, scope, deliverables, and timeframe
Building the ML solution
- Monitoring data preprocessing tasks
- Providing guidance on ML model training
- Keeping track of the solution’s development progress
- Ensuring adherence to ML implementation guidelines
- Offering recommendations on the ML model’s security and compliance
Model integration & deployment
- Selecting suitable deployment environments
- Defining an ML deployment strategy
- Offering guidance on ML model integration into corporate software
- Providing assistance with ML model scalability in the target environment
- Ensuring the ML model’s performance and security
- Assessing the adherence to ML integration and testing guidelines
Support
- Setting up a maintenance plan
- Assisting with ML model performance monitoring and issue detection
- Advising on the need for ML model retraining
- Defining a continuous improvement strategy
- Providing ongoing user training and support
Looking for a reliable tech partner for your ML project?
Our machine learning expertise
Itransition’s ML skills include computer vision-powered solutions that can capture, process, and make sense of visual inputs from multimedia content or the physical world to extract valuable information and autonomously trigger certain actions.
- Medical image analysis software
- Video surveillance solutions
- Smart inventory management tools
- Visual inspection systems
Natural language processing
The scope of Itransition's ML consulting services encompasses NLP-based tools that use complex language models to gather data from text or audio, interpret and mimic human communication, and perform real-time transcription or translation.
- ML-based conversational bots
- Spam filtering systems
- Sentiment analysis tools
- Cognitive automation software
Data mining
Itransition's consultants are well-versed in data mining solutions that rely on statistical and ML-based techniques to delve into wide sets of data, identify patterns, outliers, or relationships between variables, and derive business-relevant insights.
- Predictive analytics systems
- Anomaly detection software
- Recommendation engines
- Marketing analytics tools
Machine learning solutions across industries
Itransition provides ML consulting services to help our clients incorporate insights derived from big data into their healthcare practices and personalize treatments, achieve better medical outcomes, improve patient satisfaction, and reduce operating costs.
- AI-enhanced radiology and medical imaging
- Diagnostics and identification of high-risk patients
- NLP-powered medical assistants
- Drug discovery and development
- Automated EHR and data management workflows
Itransition equips financial institutes with ML solutions to help them attract more customers, minimize credit score risks, identify new liquidity opportunities, and automate various business processes.
- Fraud detection
- Credit scoring for loan/credit card approval
- Algorithmic trading
- Active portfolio and wealth management
- Dynamic customer segmentation and product recommendations
We offer ML consulting services to help retailers create customer-centric shopping experiences, enhance inventory management, and ensure safer shopping environments.
- Demand forecasting for inventory planning
- Social media analytics
- Marketing optimization and lead conversion
- In-store video surveillance
- Customer relationship management
Our consultants help online retailers implement ML-based tools to deliver a more interactive and personalized user experience, optimize logistics, forecast ecommerce trends, and drive sales.
- Chatbots and digital shopping assistants
- Targeted marketing
- Recommendation engines
- Dynamic product pricing
- Smart route planning and anticipatory shipping
Itransition helps companies in the real estate domain apply machine learning algorithms to detect shifting market trends, predict the price of properties in relation to market offerings, find the best investment options, and deliver superior customer experience.
- Home search and recommendations
- Property performance and market value prediction
- Automated property management
- ML-powered lead generation
- Virtual tours
.webp)
We assist manufacturing companies in implementing ML-based solutions that enable them to work out an optimal maintenance schedule, better manage fluctuations in demand and supply, and timely address anomalies in production processes.
- Equipment failure predictions
- Product development
- Automated product inspection and quality control
- Energy consumption monitoring and prediction
- Supply and demand forecasting
Itransition offers ML consulting services to help logistics companies achieve complete supply chain transparency and timely handle any issue, be it a vehicle breakdown, a sudden drop in demand, or shipping delays.
- Vehicle and equipment breakdowns prediction
- Dynamic route optimization
- Estimated time of arrival (ETA) prediction
- Supply and demand balancing
- Warehouse layout planning and workload prediction
Itransition’s team assists businesses across industries to adopt ML systems that will boost their marketing initiatives with automation and data-driven insights.
- Predictive customer segmentation
- Ad personalization for targeted advertising
- Marketing automation
- Customer lifetime value modeling
- Customer churn prediction
We share our ML expertise with financial institutions to help them and their customers identify investment opportunities, build balanced portfolios, and mitigate risk via AI-powered software.
- Stock price forecasting
- Market sentiment analysis
- Automated trade execution
- Financial fraud detection
- Autonomous stock trackers
Itransition helps educational institutions and eLearning service providers embrace ML capabilities to increase student engagement and outcomes while improving operational efficiency.
- Intelligent tutoring systems for eLearning apps
- Personalized learning paths
- Identification of students at risk of dropping out
- Elearning content translation and lesson transcription
- Virtual reality for professional training
We help agricultural organizations adopt ML technology to enable the security of remote facilities, ensure better yields, and improve pesticide effectiveness.
- Yield mapping and estimation
- Disease detection and treatment recommendations
- Classification of plant species
- Crop quality detection and classification
- Livestock health condition monitoring
Related services
Artificial intelligence
With expertise in a full spectrum of cognitive technologies, we can craft artificial intelligence solutions tailored to your requirements, streamline their deployment to your corporate scenario, and help you address emerging technical or business challenges.
Machine learning development
Itransition develops ML systems powered by supervised, unsupervised, or reinforcement learning algorithms that can autonomously learn how to complete analytical or operational tasks and progressively improve their performance through experience.
Data science
Itransition’s data scientists can help your organization gather, prepare, store, and analyze structured or unstructured data to identify patterns, anomalies, and correlations, shed light on current trends, and forecast future scenarios to enhance decision-making.
Big data
Itransition’s team provides data mapping, transformation, warehousing, analysis, and visualization services to help enterprises extract knowledge from their big data assets and selected external sources.
RPA
We create robotic process automation solutions, including software bots and smart assistants, and expand their operational scope with AI-fuelled capabilities to support your workforce in performing tedious and time-consuming clerical tasks.
Entrust your machine learning project to Itransition
Machine learning technologies we use
Our machine learning engineers have hands-on experience with major programming languages, libraries, frameworks, and third-party tools and services to build tailored ML solutions or improve the performance and resource usage of the existing ones.
Languages
Python
R
Objective-C
C++
Java/Kotlin
Libraries & frameworks
TensorFlow Keras PyTorch Scikit-Learn
Theano MXNet NumPy NLTK
Pandas Caffe MLlib SparkML
Sonnet DarkNet Catboost XGBoost
LightGBM Annoy Faiss
NvidiaDigits OpenCV Microsoft Cognitive Toolkit
Network architectures
Neural radiance field (NeRF) Convolutional neural network (CNN) Recurrent neural network (RNN) YoloNet
Skeleton detection U-Net Generative adversarial network (GAN) AlphaPose
Pose2Seg RetinaFace DBSCAN
Task types
Clustering algorithms Regression algorithms Classification algorithms
AI & ML services
Amazon SageMaker Amazon Rekognition Amazon Lex Amazon Polly Amazon Transcribe
Amazon Comprehend AWS Deep Learning AMIs Azure Machine Learning Azure Cognitive Services Azure AI Bot Service
Azure Conversational Language Understanding Google AI Platform Cloud Vision API Cloud Natural Language AI Cloud Speech-to-Text API
DialogFlow Google Cloud AutoML NVIDIA CUDA OpenAI API
Data integration tools
Azure Data Factory Azure Functions Azure Event Grid Azure Event Hubs Azure Databricks Microsoft SQL Server Integration Services
AWS Glue AWS Data Exchange Apache Nifi Talend Informatica PowerCenter
Dell Boomi MuleSoft Anypoint Platform IBM InfoSphere Information Server Oracle Data Integrator SnapLogic
Precisely Striim Pentaho Fivetran Matillion
Data storage services
Azure Blob Storage Azure Data Lake Storage Azure SQL Database Azure SQL Database Elastic Pool Azure SQL Managed Instance Azure Cosmos DB
Microsoft SQL Server Amazon S3 Amazon Redshift Amazon Aurora Amazon RDS
Amazon DynamoDB Amazon ElastiCache PostgreSQL MySql Oracle
Google Cloud Storage IBM Cloud Object Storage SAP HANA SQLite Teradata
Data analytics platforms
Azure Analysis Services Azure Stream Analytics Azure Synapse Analytics Microsoft SQL Server Analysis Services Microsoft Power BI
Grafana QlikView Tableau Sisense
Amazon Athena Amazon Redshift Amazon Kinesis Data Analytics Google Cloud Storage
IBM Cloud Object Storage SAP HANA SQLite Teradata
Data visualization tools
Datawrapper Chartist.js
matplotlib seaborn
bokeh Plotly
Altair ggplot
Infogram Google Charts
Fusion Charts D3.js
Excel
Benefits of turning to ML consultants
Optimized investment
Our machine learning consulting company can help your organization select an optimal tech stack and identify use cases requiring ML instead of conventional solutions.
Streamlined project planning
With the support of a machine learning consulting firm, you can set up a suitable ML development and implementation roadmap and accurately define timelines, budgets, tasks, teams, and iterations.
Faster rollout
Our ML consultants can complement your in-house experts to complete your ML project within a shorter time frame without recruiting and training additional talent.
Lower business risk
A team of ML consultants will help you address potential business or technical challenges (lack of training data, ML model bias, non-compliance, etc.) and mitigate related risks.
ML consulting FAQ
What engagement models do you offer?
For machine learning projects, we offer the following engagement models:
- Dedicated team
We provide a team of selected ML experts for long-term collaboration. The price depends on the time spent to complete the defined tasks.
- Time and material
Itransition provides ML consultants for a set fee, with the final cost depending on person-hours and materials spent on your project.
- Fixed-price
Our ML specialists will join your project for a fixed price according to an approved scope, development budget, and timeline.
How do you integrate the ML solution with our legacy systems?
At the discovery stage, we analyze your existing technology environment and, drawing on this information, conceptualize the ML solution and define its components. If you want a fully-integrated solution, we can perform the necessary integrations; otherwise, we will pass all the necessary information and documentation to your in-house team.
How do you guarantee the safety of our information?
We make sure your information is processed according to the industry’s best practices and protected with solid cybersecurity measures, including role-based data access, multi-factor authentication, 24/7 user activity monitoring, and data exchange encryption.
Do we need the infrastructure to train ML models?
No, you don’t. Itransition can train machine learning models on local servers with increased CPU power as part of our service offering.
What if we don’t have enough data for training models?
To handle the lack of data and meet established objectives, our machine learning experts help you set up the data collection and generation processes, complementing your corporate data assets with external sources if necessary. We can also leverage cloud-based services providing pre-trained models.
Service
ML services and solutions from certified machine learning experts
Get ML consulting and development services from machine learning experts. Proven expertise in artificial intelligence, machine learning, and data science.
Insights
Machine learning statistics
Itransition presents the ultimate list of machine learning statistics: market data, ML adoption by industries, economic impact, investments, and other facts.
Insights
Top machine learning use cases and industry applications
Discover top machine learning use cases and their examples across industries and learn how they make a difference for the companies.
Insights
AI use cases: 3 rules to find the right one for your business
One of the main barriers to AI adoption is identifying the right AI use cases. Find out the best practices to make it less challenging.
Case study
ML PoC for aquatic environment analysis
Learn more about a PoC of an ML-based plankton detection and classification solution we developed, proving the suggested approach.
Insights
Supervised vs unsupervised machine learning: a selection guide
Find out how supervised and unsupervised learning work, along with their differences, use cases, algorithms, pros and cons, and selection factors.