SERVICES
MLOps Services
Start gaining value from machine learning models. Leverage our MLOps services to ensure efficient implementation of AI solutions.
We help you maximize time-to-value while ensuring the most efficient budget allocation. Whether you need continuous monitoring for your ML services or efficient pipelines to support them, we’re here to help.
THE PROBLEMS WE SOLVE WITH MLOPS
With our MLOps as a service offering, you get efficient solutions to the following challenges.
Models stuck in development
A common problem in ML development is that many machine learning models never make it past the lab stage. We help you solve this issue by streamlining deployment to ensure that your models deliver value in real-world environments.
Slow workflows
Often, low speed and manual management of pipelines are significant obstacles to automation. We help you accelerate iterations and reduce time-to-market by establishing highly efficient, automated, and secure pipelines.
Lack of monitoring and reliability
Degradation of ML models is a common problem that can reduce their efficiency and even lead to costly mistakes. To help you avoid such an issue, we establish continuous monitoring that helps you control the accuracy and performance of your model.
Scaling problems
In many cases, promising models fail under production loads. Adapting your ML models to scaling challenges might be an issue. We are here to help you design scalable and dynamic ML infrastructures that grow with your business.
Data management issues
The quality of machine learning models often suffers because of disorganized or inconsistent data pipelines. With our MLOps as a service offering, you will get support with building reliable data flows for efficient model learning.
Compliance and governance risks
ML models are powered by significant amounts of data, including sensitive information. To help you avoid compliance issues and security breaches, we help you establish solutions for monitoring and efficient data governance.
OUR MLOPS SERVICES AND SOLUTIONS
Model deployment and orchestration
We help you successfully transition from experimentation to production. Our specialists use advanced frameworks to ensure that models are properly integrated into your systems.
This will help you reduce downtime and operational risk. Our orchestration tools help you enable automated scaling and rollback mechanisms. We also ensure smooth version management to offer you greater flexibility.
Continuous monitoring and optimization
Changes in data or environments can negatively impact your model performance over time. To help you avoid such an issue, we will establish continuous monitoring.
This will allow you to detect anomalies, track KPIs, and trigger automated retraining. As a result, you will avoid ML model degradation and keep it relevant and reliable for your business.
Automated pipelines and CI/CD for ML
Our MLOps specialists help you reduce the amount of manual workflows that might be slow and prone to errors. Our specialists design automated CI/CD pipelines tailored to ML to cover data ingestion, feature engineering, model training, and deployment.
As a result, you can experiment and develop new ML models many times faster.
Data management and governance
With our MLOps consulting services, you will establish efficient data management and governance. We help you implement data pipelines and validation frameworks that help you establish and maintain efficient data governance policies.
By achieving consistency, traceability, and compliance in your data practices, you set a reliable foundation for innovation.
Scalable infrastructure design
We help you build a scalable and efficient infrastructure tailored to your needs. Our specialists can build cloud-native containerized and serverless solutions with a strong focus on ML model development.
As a result, you will get an excellent combination of cost-efficiency, high availability, and innovation for your business needs.
Security and compliance integration
We help you ensure robust security of your infrastructure to safeguard your ML models and data powering them. Our team helps you establish the best security and monitoring practices for your ML workflows.
This will help you stay compliant with the major regulations across industries, such as GDPR, HIPAA, etc. We also provide compliance-centric MLOps consulting services.
Industries
At AppRecode, we collaborate with a diverse range of industries to deliver tailored digital solutions that solve real-world challenges. From mobility and travel to healthcare, fintech, e-commerce, and beyond — we bring deep expertise and a flexible approach to every project. Whether you’re a startup or an enterprise, we help you move faster, scale smarter, and build with impact.
Telecom
Automotive
Transportation and Logistics
Retail
Finance
Security
Healthcare
Business management
InsuranceREAL RESULTS: DEVOPS INFRASTRUCTURE MIGRATION
Client challenge: A provider of AI-powered contact center software wanted to modernize its infrastructure while preserving critical AI capabilities and possibilities for continuous improvement of ML algorithms.
Our approach: We prepared a detailed work breakdown structure (WBS) that served as a roadmap during an efficient migration from EC2 instances to the Amazon Kubernetes Service platform, which ensures excellent manageability and security crucial for ML development.
Results:
Preserved mission-critical AI functionality of the customer’s platform
Holistic monitoring system for all the customers’ assets
Benefits of AWS services and possibilities for convenient ongoing upgrade of the infrastructure
Enhanced system flexibility and agility
CI/CD environment based on GitHub Actions and ArgoCD, powered with strong automation algorithms
HOW WE WORK
Phase 1: Assessment & strategic planning
- Analysis of current ML workflows, infrastructure, and data pipelines
- Analysis of gaps, risks, and optimization opportunities
- Creating an MLOps roadmap tailored to business goals
Phase 2: Infrastructure & pipeline setup
- Developing a scalable, cloud-native, or hybrid infrastructure
- Creating CI/CD pipelines for data, training, and deployment
- Automated workflows for versioning, testing, and integration
Phase 3: Deployment & integration
- Containerization and orchestration for ML models
- Integrating models into existing applications and systems
- Rollback and safe release strategies
Phase 4: Monitoring & optimization
- Setting up continuous monitoring for model degradation and performance
- Automating alerts, retraining, and fine-tuning processes
- Ensuring regular reporting and actionable insights
Phase 5: Governance & compliance
- Embedding security and compliance policies into ML workflows
- Audit trails and model explainability frameworks
- Ensuring compliance with industry-specific regulations
Our DevOps Team
If you’re looking to hire full stack developer talent, our team offers experienced professionals skilled in front-end and back-end technologies for seamless project execution. With years of experience and a proven track record, our team ensures seamless integration, automation, and optimization of your development and operations processes.
4.4
Our decision to work with Relevant was based on their understanding of our industry, the depth of their technical capabilities, and a real commitment to building a true partnership model. We believe that the Relevant team is ready to go the extra mile for us to help us achieve our goals and expand our business globally.
Dr Liam Terblanche
Founding member of Scriversi
CTO/CIO of other companies in the ICT space
4.0
Working with Apprecode was a great experience. They provided a professional and efficient service and created individual decision.
We are happy with the AWS solution. Every feature was given attention to make sure it worked as required.
We recommend Apprecode and look forward to continued cooperation.
Alex Should
Manager of “REW” company
5.0
I’ve had the pleasure of using Apprecode for cloud migration and management. They’re knowledgeable and professional, and their team is experienced. They go the extra mile and provide helpful advice and guidance. I’ve had a great experience with Apprecode and recommend their services.
Austin Copeland
Director of Finance and Operations at REW Technology
5.0
The DevOps services provided by Apprecode are comprehensive and cover all aspects of a project, from planning to deployment. They worked closely with me to assess my needs and develop a strategy to best address them. The team was able to quickly create a deployment plan that was tailored to my specific requirements.
Bob Whirley
Utopic Software
4.0
I’m extremely satisfied with Apprecode’s DevOps services. Their team was knowledgeable, and professional and gave prompt feedback. I recommend them for any project.
Michael Lazor
CEO of “SPSoft” Company
4.0
AppRecode has been instrumental in helping us build community-driven solutions and generate ideas for future products. Their team is highly responsive and professional, and most members are certified in at least one cloud platform. Working with AppRecode has been a seamless experience, and their expertise in DevOps as a Service has significantly contributed to the progress of our project. We recommend Apprecode and look forward to continued cooperation.
Dmitry Fonarev
CEO and Founder of “Kubeshop” Company
Machine learning is the future, and implementing the infrastructure ready for ML experimentation and adoption is a very important step for a company that needs to prepare for the future. With MLOps service, organizations set a lasting foundation for their long-term ML implementation goals.
WHY CHOOSE US
Significant experience in ML development, cloud architecture design, and DevOps services
Focus on fast time-to-value with AI initiatives
Deep knowledge of common ML degradation aspects and proven practices for mitigating these risks
Tailored MLOps solutions and best practices tailored to different business needs
Best automation and scalability practices for pipelines
Built-in security, compliance, and data governance
Monitoring solutions and continuous support
EMBRACE THE POWER OF MACHINE LEARNING WITH OUR MLOPS SERVICES
Schedule a free consultation with our experts to assess your needs and find the best MLOps strategies tailored to your business goals.
FAQ
MLOps helps you bridge the gap between data science and IT operations. You receive a scalable infrastructure with highly automated pipelines and established workflows for ML model development and deployment.
With the MLOps service offering, you get tailored platforms and managed services that help you build ML-ingested infrastructure from scratch.
Choosing MLOps solutions might be a more costly and time-consuming option. It will require you to hire an in-house team and spend time on establishing the tooling and the infrastructure.
MLOp gives you better control over your ML development and adoption efforts across environments. You get standard workflows, automated pipelines, and tools for monitoring.
We provide custom tools and monitoring configurations, enhanced with efficient dashboards, to help you track the performance of your ML model. This allows you to detect anomalies and identify cases when your ML model performance degrades due to data drifts or any other issues.
At AppRecode, we apply a variety of tools to ensure efficient MLOps service delivery. While everything depends on your business needs, the list of technologies often includes Kubernetes, MLflow, Airflow, and Vertex AI.
Everything depends on project complexity. It may take from several weeks to a few months to implement MLOps services at the enterprise level.
Yes, we keep supporting you after implementing MLOps workflows. In particular, we can provide continuous support and monitoring. All to help you keep your ML models working safe and dry in the long run.
Rate Apprecode as Your Partner
6 ratings, average 4.9 out of 5
