MLOps Services
MLOps Services
Coherent Solutions delivers end-to-end MLOps services to help businesses streamline AI operations, scale model deployment, and ensure seamless integration with their existing systems.
Request Free ConsultationEnd-to-End MLOps Services
MLOps Consulting Services
Boost your ML capabilities with customized MLOps strategies. We design efficient frameworks, modernize models, and streamline deployment for seamless integration and ongoing performance.
MLOps Maturity Assessment
Assess your MLOps maturity by evaluating strengths, weaknesses, and improvement areas across the ML lifecycle. Focus on tools, infrastructure, and governance to refine your strategy.
ML Pipeline Development
We specialize in building automated ML pipelines that efficiently process data and code, ensuring accurate models and streamlined performance throughout the ML lifecycle.
MLOps Model Deployment
With extensive experience deploying ML models on AWS, Azure, and GCP, we optimize performance, scalability, and availability, ensuring seamless and reliable integration.
Model Monitoring & Observability
We implement advanced observability tools to monitor ML models, data, and pipelines, ensuring consistent performance and maximizing ROI on your AI investments.
Data Engineering and Management
We provide expert guidance on acquiring, cleaning, and processing data to ensure you get optimized datasets that enhance ML model performance and minimize errors.
CI/CD for Machine Learning
Our CI/CD services accelerate MLOps model deployment by automating pipelines and streamlining development, reducing time-to-market and driving business growth.
Model Governance & Compliance
We enhance ML model security and integrity with robust governance strategies, ensuring data confidentiality, regulatory compliance, fairness, bias detection, and performance evaluation.
MLOps Solutions Tailored to Your Domain
We provide MLOps services across a wide range of industries, delivering customized solutions that meet the unique needs of each domain. From manufacturing and healthcare to retail, we create systems that optimize performance, scalability, and efficiency.
Manufacturing & Logistics
Demand Forecasting • Inventory Optimization • Quality Control • Predictive Maintenance • Supply Chain Management
Healthcare & Life Science
Clinical Decisioning • Drug Discovery • Personalized Medicine • Healthcare Operations Optimization • Fraud Detection • Regulatory Compliance
Education & eLearning
Personalized Learning • Student Success Prediction • Recommendation Systems • Administrative Efficiency • Educational Research
Product & Tech Companies
Predictive Analytics • Customer Support • Cybersecurity • Operational Efficiency
Retail & eCommerce
Personalized Marketing • Demand Forecasting • Dynamic Pricing • Supply Chain Optimization • Sentiment Analysis
Financial Services
Risk Management • Algorithmic Trading • Customer Insights • Compliance Automation • Fraud Detection
MLOps Technologies We Employ
CI/CD and Containerization Model and Data Versioning Model Training Automated Machine Learning Model Deployment
CI/CD and Containerization
We use advanced practices and technologies to accelerate the development, deployment, and management of machine learning models, ensuring consistency, scalability, and reliability in production. Key technologies include:
• CI/CD: Jenkins, GitLab CI/CD, CircleCI, GitHub Actions, ArgoCD
• Containerization & Orchestration: Docker, Kubernetes, ECS, EKS, AKS
Model and Data Versioning
We implement robust versioning practices to ensure reproducibility, traceability, and consistency across the machine learning lifecycle. These practices enhance collaboration, maintain data integrity, and improve the reliability and transparency of model deployments in production. Technologies we use:
• Model Serving: MLflow, KubeFlow, TensorFlow Serving
• Data Versioning: DVC (Data Version Control)
Model Training
Model training involves using algorithms and data to identify patterns, make predictions, and optimize decision-making. This critical phase in the ML lifecycle focuses on developing and fine-tuning models to achieve accuracy, performance, and reliability. Our tools and frameworks:
• Frameworks: TensorFlow, PyTorch, Ray, MLFlow, KubeFlow
• Libraries: Sklearn, XGBoost
Automated Machine Learning
AutoML automates the end-to-end process of applying machine learning to real-world problems, including model selection, feature engineering, hyperparameter tuning, and deployment. It empowers users of all skill levels to build high-quality models with ease. AutoML platforms we use:
• Google Cloud AutoML
• Azure AutoML
• H2O
• AutoML
• DataRobot
Model Deployment
We make ML models production-ready, enabling them to generate predictions or classifications from new input data. This involves preparing trained models and their dependencies for seamless integration into existing applications and software systems. Model serving tools we use:
• KubeFlow
• Seldon
• RayServe
Our Experts
Anton Cheplyukov
AI Practice Lead
Andrey Tkachenya
AI Engineering Lead
Vladislav Svetlakov
Machine Learning Engineer
Stanislav Bychkovsky
Machine Learning Engineer
Looking for MLOps Experts?
Streamline your ML operations with our end-to-end solutions, from model deployment to seamless integration. Discover MLOps benefits like faster time-to-market, reduced operational costs, and improved model reliability. Contact us today to learn more.
Request Free ConsultationSuccess Stories Delivered by Us
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Your Trusted MLOps Consulting Partner
Expert Digital Engineering
With 30 years of experience, we provide comprehensive MLOps services that simplify model deployment, enhance operational efficiency, and ensure seamless integration.
Comprehensive Tech Stack
With a dedicated team of AI engineers, we leverage both well-known and cutting-edge technologies to deliver robust, scalable AI solutions tailored to your business needs.
Industry Experience
As an experienced MLOps provider, we’ve successfully delivered AI-driven solutions across diverse industries, including healthcare, finance, retail, and manufacturing.
Secure & Agile Development Process
From model training to deployment, we deliver a secure and agile MLOps process, ensuring scalable AI solutions with top performance, reliability, and robust data protection.
Our Clients Say It Best
We focus on delivering results that matter. See what our clients have to say about working with us.
Flexible Engagement Models
Consulting
Not sure where to begin with MLOps? Our consulting services help you craft a clear ML strategy, evaluate your current processes, and identify opportunities for optimization.
Dedicated Team
Enhance your MLOps with a dedicated team of experts. Our specialists collaborate with your in-house team to implement robust MLOps practices, ensuring scalability and reliable performance.
Professional Services
Whether optimizing model deployment or ensuring industry compliance, our professional services enhance efficiency, scalability, and reliability in your AI/ML operations.
Product Development
Turn your ideas into reality with our ML-focused product development. From concept to deployment, we design, build, and optimize machine learning products tailored to your business needs.
AI Solution Accelerators
Need to validate ideas with AI quickly? We help you develop and deploy POCs or POVs for solutions like churn prediction, user behavior analytics, or image classification. Our tailored approach combines pre-built frameworks and custom development, ensuring fast, reliable results while aligning with your business needs.
Accelerate Your AI ProjectFrequently Asked Questions
What is MLOps and how can it benefit my business?
MLOps (Machine Learning Operations) is a set of practices that streamline the deployment, monitoring, and maintenance of ML models in production. It helps your business by ensuring models run reliably at scale, accelerating time-to-market, improving performance, and reducing costs, ultimately driving efficiency and consistent results.
How can MLOps improve the performance of my machine learning models?
MLOps boosts model performance by automating tasks like data preprocessing, training, and deployment. It also ensures continuous monitoring and retraining, keeping models accurate and aligned with evolving business needs, resulting in more reliable and adaptable AI solutions.
What kind of businesses can benefit from MLOps services?
MLOps benefits businesses across industries like finance, healthcare, retail, and manufacturing. Any organization using data-driven decision-making or AI can leverage MLOps to improve the efficiency, scalability, and reliability of their machine learning operations.
How do you ensure data security and compliance in your MLOps processes?
We prioritize data security and compliance by using strong governance practices like encryption, access controls, and anonymization. We also adhere to industry standards such as GDPR and CCPA, ensuring all data handling is secure and compliant.
What is the typical timeline for implementing MLOps in an organization?
The timeline for MLOps implementation depends on your project’s complexity and existing infrastructure. Typically, a basic setup takes a few weeks to a few months, covering requirement analysis, data pipeline setup, model development, deployment, and establishing monitoring and governance frameworks.
Can you integrate MLOps with our existing IT infrastructure and tools?
Yes, we can seamlessly integrate MLOps with your existing IT infrastructure and tools. We assess your current systems—whether cloud, on-premises, or data storage—and ensure smooth compatibility with your workflows and CI/CD pipelines.
Get a Free Consultation with Our Experts!
Simply fill out our contact form below, and we will reach out to you within 1 business day to schedule a free 1-hour consultation covering platform selection, budgeting, and project timelines.
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Here's what happens next:
- Our sales rep will contact you within 1 day to discuss your case in more detail.
- Next, we will arrange a free 1-hour consultation with our experts on platform selection, budgeting, and timelines.
- After that, we’ll need 1-2 weeks to prepare a proposal, covering solutions, team requirements, cost & time estimates.
- Once approved, we will launch your project within 1-2 weeks.