AI Implementation Made Easy: 7 Smart Steps to Scale Your Business
AI Implementation Made Easy: 7 Smart Steps to Scale Your Business AI implementation has moved from being an innovative experiment to becoming…
Azure Machine Learning Services
Data scientists can now swiftly build and deploy models for accelerated innovation with our Azure Machine Learning Services.
Faster ML model training
Scalable AI compute power
Optimize Costs with Smart Solutions
24/7 Support and Maintenance
30+
Azure AI Specialists Delivering Advanced Intelligent Automation
70%
Faster Outcomes Enabled by Azure Machine Learning
70+
AI-Driven Azure Solutions Designed for Scalable Global Innovation
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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Helping business building technology
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.
Predictive Maintenance
Using Azure Machine Learning and IoT integration; we forecast equipment failures before they happen. This helps minimize downtime, optimize asset performance, and lower maintenance costs through proactive maintenance scheduling.
Demand Forecasting
Azure AI models analyze historical and real-time data to predict demand trends accurately. These insights enable smarter inventory management, optimized resource allocation, and improved supply chain efficiency.
Sentiment Analysis
With Azure Cognitive Services, businesses can analyze text and voice data to detect sentiment and emotion. This helps improve customer engagement, refine marketing campaigns, and enhance overall brand experience.
Our Technologies
Why Choose Bloom for Azure Machine Learning 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
Enterprise AI Development for a German Client
Industry: Manufacturing & Industrial Services
Location: Germany
The Challenge
The client relied on manual analysis and fixed rules to make important business decisions. This made it hard to react quickly, spot issues early, and plan accurately, while still meeting strict EU data privacy regulations.
The Solution
We built custom AI solutions that analyse data, predict demand, and highlight risks automatically. These insights were integrated into the client’s existing systems, helping teams make faster, smarter decisions with full transparency and GDPR compliance.
Read Case Study >
AI-Powered Procurement Optimization for a Global IT Enterprise
Industry: Information Technology
Location: North America, Europe & Asia-Pacific
The Challenge
Purchase requests were created manually across regions, often describing the same items in different ways. This made it hard to combine orders, slowed procurement, and reduced negotiation power with vendors.
The Solution
We built an AI-driven system using Azure AI Foundry that understands purchase requests, groups similar items automatically, and suggests consolidated requests. This helped procurement teams work faster, reduce manual effort, and negotiate better deals, while keeping full control and transparency.
Read Case Study >
AI-Driven Business Insights for a Multi-Region Indian Enterprise
Industry: Sales & Operations
Location: India (Multi-Region)
The Challenge
Business decisions were mostly based on past reports and manual spreadsheets, making it hard to react quickly to market changes.
The Solution
We built an Azure AI–powered analytics platform that turns business data into clear forecasts and early warnings. Teams can spot risks sooner, plan better, and make faster decisions without relying on complex reports or manual analysis.
Read Case Study >
Intelligent Document Processing with Azure AI
Industry: Document-Driven Operations
The Challenge
The team spent too much time manually reading and entering data from invoices, PDFs, and scanned documents. This caused delays, errors, and made it hard to get useful insights from the data.
The Solution
We used Azure AI to automatically read documents, extract important details, and understand text like customer notes and vendor comments. This reduced manual work, improved accuracy, and helped the business process documents faster and with more confidence.
Read Case Study >
Predictive Insights with Azure Machine Learning
Industry: Data-Driven Operations
The Challenge
Even with modern systems in place, the business relied on past reports and manual analysis. This made it hard to predict trends, spot risks early, or make fast decisions.
The Solution
We built a secure Azure Machine Learning platform that turns existing data into future-focused insights. The system predicts demand, flags unusual patterns, and shares clear insights through dashboards and apps that teams already use.
Read Case Study >
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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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