Azure Machine Learning Services
Data scientists can now swiftly build and deploy models for accelerated innovation!
Get AI-powered services that allow businesses to benefit from the power of advanced algorithms to learn from data and make recommendations and predictions.
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Our Machine Learning Services in Azure
Get a comprehensive cloud service for building, training, and deploying machine learning models, and give your business a competitive edge!
Microsoft Azure Machine Learning (Azure ML Studio)
An end-to-end platform to build, train, and manage machine learning models. Our Azure machine learning services are associated with code-first and no-code tools, aiming for hassle-free collaboration and deployment.
Azure Cognitive Services
With our pre-trained AI tools that provide applications with vision, speech, language, and decision capabilities, you can just use them without building any model.
Azure OpenAI Service
Our Azure ML services give access to powerful language models like GPT-4 via Azure. It makes developing chatbots, summarizing texts, or writing codes so simple.
Azure Databricks
Collaborative data platform for big data and machine learning built over Apache Spark. It is good when it comes to handling big datasets and creating scalable ML models.
Azure Synapse Analytics (with ML)
Merges data warehousing and analytics with in-built ML. It enables you to do all your analysis and model scoring straight from SQL.
Azure Data Science Virtual Machines (DSVM
Pre-configured VMs, fully loaded with ML and Data Science Tools, are a great choice for testing models on the fly, research, or rapid prototyping.
Azure AutoML
Pick the best models and tune them for your data automatically. This tool is geared towards people with little to no coding experience who want to see tangible results fast.
Azure Kubernetes Service (AKS) for ML
Our Microsoft machine learning solutions Provide container-based and Kubernetes-based deployment of ML models on a large scale. Use it whenever you require real-time prediction and flexible hosting.
Azure Arc for ML
Extends Azure machine learning services to on-prem or other cloud services. This is good for hybrid cloud scenarios and also for complying with data residency requirements.
Azure Machine Learning Services Delivery Pipeline
We help businesses automate the machine learning lifecycle with our Azure machine learning services. We have covered everything from data preparation to model deployment and monitoring! Here are the prerequisite steps in the AI service delivery lifecycle toolkit.
Understanding Needs
First, discovery workshops, stakeholder interviews, and process reviews are organized to elucidate business opportunities and user expectations. This allows for the determination of a suitable ML use case and the definition of the solution scope, technical requirements, and expected outcomes.
Typical Team Members:
Business Solution Consultant
ML Solution Architect
Preliminary Data Assessment
Our experts then explore the datasets made available between agents or third-party sources to assess whether they are suitable for this project. This includes data cleaning, filling of missing values, dimensionality reduction, and designing a preprocessing workflow to aid the analysis as a part of our Azure machine learning services.
Typical Team Members:
ML Solution Architect
Data Scientist or ML Engineer
Machine Learning Solution Design
Following business needs, a machine learning architecture is designed, and the best algorithms or tools are shortlisted and selected to comprise the complete set of technologies chosen. If a PoC is needed, objectives, methods, and success criteria are laid out in detail at this stage, and an exact budget with timescales is attached for approval.
Typical Team Members:
Business Solution Consultant
ML Solution Architect
Machine Learning Model Development
The Data/ML engineers prepare and clean data for labeling and transformation and start training models using various machine learning techniques, such as supervised learning, reinforcement learning, and others. Model assembling might be utilized to improve accuracy while ensuring security and compliance.
Typical Team Members:
Data/ML Engineer
Project Manager
Business Analyst
QA Engineer
Deployment and Integration
With the deployment setup selected, an integration strategy will be used to install ML into current systems. Following testing, the solution is released into production, ensuring it performs smoothly, scales readily, and remains secure.
Typical Team Members:
MLOps Engineer
Data/ML Engineer
Project Manager
QA Engineer
Continuous ML Support
Monitor the model’s performance and retrain with new data generated for actual use simultaneously without interrupting operations; both user training and documentation are provided. Formulate a strategy for continuous improvements if required.
Typical Team Members:
Support Engineer
Project Manager
Our Customized Machine Learning Solutions
Our custom machine learning solutions are customized AI models designed to meet your business needs.
Predictive Analytics
Utilizing historical data to predict outcomes and trends for the future. Depending on the scenario, our Azure machine learning services customize ML models for your business to aid in planning marketing, risk, supply chain, and customer service.
Recommendation Systems
Our algorithms consider user activities to enhance engagement and conversions in real-time, allowing personalized suggestions for products, content, or services.
Video and Image Analysis
Derive insights from visuals for faster, automated operational decisions. We train the model to detect objects and faces or identify defects for applications such as security monitoring, diagnostics, and quality inspections.
Natural Language Processing (NLP)
Allowing systems to understand and act upon human language, our applications of NLP include text analytics, content classification, and sentiment tracking to support enhanced decision-making and automation.
Speech Recognition
Convert the spoken tongue into digital data that is available for use. Our speech models recognize accents and take context into account for real-time transcription services and voice-enabled applications.
Fraud Detection
Detect suspicious patterns and prohibit fraudulent activities beforehand. Using domain-wise ML models for anomaly detection and risk management in real-time.
Customer Segmentation
Group customers by behavior, value, or profile. We use clustering and predictive analytics for targeted marketing and retention campaigns.
Computer Vision
Train computers in how to interpret and see visual input. We engineer vision systems tailored to your business requirements, from object detection to image classification.
Document Processing
Converting unstructured files into structured and actionable data. Our solutions extract key information from scanned documents or PDFs using OCR and AI.
Our Technologies
Why Choose Bloom for Azure Migration Services?
Seamlessly transition to the cloud with Bloom’s expert-led Azure migration strategies. We ensure minimal disruption, maximum efficiency, and future-ready scalability.
Azure ML Experts
The Azure Machine Learning suite brings forth a new set of opportunities and challenges. Our teams use the latest tools on Azure to build smart, secure, and scalable ML solutions.
Business Objectives- Focused
Our Azure machine learning services don’t just focus on ML modeling. We ensure it addresses key problems, such as improving sales, cutting costs, or minimizing risks.
Drive Efficiency and Innovation with End-to-End ML Services
Full-Service Support
With assistance from associating needs, building, launching, and providing support for the ML solution, we put everything under one roof.
Industry Experience
We tailor the ML solution to your industry and data needs in retail, banking, health, manufacturing, or any field. We provide one of the most renowned Azure machine learning services.
Simple and Clear Process
We will work closely with you throughout the project. You will always be in the loop about what is happening, and your feedback will guide the project.
Post Launch Support
After Going live, our ML solution receives all the necessary monitoring maintenance and enhancements to remain useful.
Client Feedback
Enhance your stakeholder’s experience by using the latest trending technologies
“The deployment team at Bloom has been very professional in taking over the system support from the previous iOS vendor. They are able to identify the key operational issues and fix them in record time with quality. Helped us achieve our business goals smoothly.”
Birju Patel
Founder & CEO – Deliverr.ca
“It has been our pleasure working with Bloom for many years. We like to take this opportunity to convey our appreciation to team Bloom helping us shape our product development journey with Smazing.”
Karan Punjabi
CEO and Founder – Smazing
“We are very pleased to have partnered with Bloom. Bloom has a good Professional Services/ Human resources team for providing IT consultants. Bloom was very flexible with the approach and fulfilled our requirements within the deadline.”
Manish Yadav
Manager, People Development – GlobalLogic
Success Stories
Managing Software innovation
- SaaS
- Database Management
Client’s old system was crowded and complicated, leaving their users frustrated and unaware of where to find the content important to them. We needed to simplify the navigation of the system for both existing as well as new users. To facilitate the reduction of screens in the new system and streamline the user-experience, our team needed a way to examine the relationship between services, keywords and concepts we uncovered in our initial strategy meeting.
We developed a web app solution with .NET based tech stack. App offers all features with an ease of use to its users, two of the salient features are Streamlined Interface combined into one seamless online experience with easy content management, and effortless navigation. Advance search and filter improve user experience, promotes services, and encourage easier information retrieval.
Internal Approval System
- Web App
- Mobile App
- Consulting
The client wanted a digital approval system in which various employees from different business units can easily create approval requests. The app should enable them to seamlessly collaborate and give approvals/comments on-the-go for saving time and fasten the overall process.
Bloom created unique, responsive, and user-friendly web and mobile apps to streamline the approval system. The mobile app is intended for enabling users to approve requests on-the-go. We digitized the forms, and now they can be filled via the web app that made it easier to collaborate and maintain data quality. Roles to employees were assigned based on their active directory groups for seamless login and maintenance.
Social Network with Rewards
- Smazing is a unique social network which allows you to share and explore the world through Live Broadcasts and Viral Videos.
- Clubbed with a high-quality communication suite, you can use to enjoy a variety of chat/call options
- Smazing Marketplace where business owners can list and promote their products/brands
- Users can earn Smazing Loyalty Points (SLPs) by watching promoted video ads and earn deals on the Smazing app
- View featured content of the most popular products and services
- A business owner (local or online) you can promote it with discount deals on the app with Video Ads and get wide visibility and traction
- Earn SLPs to earn product discounts on deals
Frequently Asked Questions
What are Azure Machine Learning Services?
Azure machine learning can be defined as a full-fledged machine learning platform that fosters language mode deployment and fine-tuning. If you are looking for Azure machine learning consulting services, you can contact us today!
What is Azure Machine Learning Studio?
It is one of the most sought-after resources in Azure Machine Learning services. It provides a centralized place for developers and data scientists to work with all the required features for training, building, and deploying ML models.
What is Azure Automated ML?
Automated ML makes building machine learning models easier and more accessible, allowing users of all skill levels to create complete ML pipelines for different types of problems.
What are Azure machine learning ops?
MLOps is a practice that simplifies the development and deployment of ML models and AI workflows. Get started easily with Azure Machine Learning Studio.
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