SERVICES
MLOps Consulting
The process of creating a machine learning model proves to be straightforward. The main challenge of running the system in production mode lies in its ability to maintain reliable operation.
Research indicates that more than 85% of AI pilots fail to achieve production status because their development pipelines lack essential components for reproducibility and automated deployment and monitoring systems.
Our MLOps consulting services bridge this gap through the combination of software engineering discipline with data science expertise. Our team assists you in creating prediction systems which maintain their accuracy throughout daily operations while your data and user activities undergo modifications.
Our MLOps Consulting Services
Our MLOps consultants offer architecture design, pipeline automation, governance, cost optimisation, and much more:
Our MLOps architecture consulting service develops flexible systems which connect to your existing cloud-based and on-premises infrastructure.
Our team of experts uses automation to handle all stages of data processing and model development including training and evaluation and deployment and retraining for model updates.
The team uses MLflow and DVC and Weights & Biases tools to track experiments and evaluate models and handle registry management.
The service includes dashboard functionality which enables alert systems to identify when data patterns shift or when model performance worsens.
Our team of experts implements secrets management alongside access controls and audit logs and compliance checks to fulfill GDPR and HIPAA regulatory requirements.
The team implements three cost reduction strategies which include optimizing compute resource usage and implementing spot instance technology and job scheduling optimization.
Who We Work With
We work with Heads of Data Science and ML leads who need to turn research into reliable, production-ready systems across multiple initiatives.
We partner with CTOs and engineering leaders to integrate machine learning into products while keeping cost, security, and operational risk under control.
We also support Platform Engineering, MLOps/DevOps teams, and regulated enterprises with shared services, audit-ready workflows, and clear traceability for compliance.
Client Challenges We Solve as a MLOps Consulting Company
Models stuck in PoC. Without pipelines, promising prototypes often fail to reach users.
Lack of reproducibility. Inconsistent environments make it impossible to recreate results.
Manual deployments. Copying models by hand can lead to errors and downtime.
No monitoring or drift detection. Models degrade silently, resulting in inaccurate predictions and lost revenue.
Uncontrolled infrastructure costs. Training jobs and inference servers run without optimisation, inflating bills.
Business Value
Successful MLOps adoption drives measurable results:
Teams using MLOps can ship models 2–5 times faster than their peers.
Organisations report a reduction of up to 8 times in ML infrastructure spend after adopting MLOps.
Enterprises report returns of 300%–2,000% from MLOps adoption.
If you want to turn your experiments into reliable products, talk to our experts. We will help you identify quick wins and plan a scalable MLOps platform.
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.
Reviews
4.4
Our decision to work with AppRecode 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 AppRecode`s 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
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: MLOps Deployment For In-Game Personalization
Client challenge:
An online gaming company wanted to personalize in-game offers, but the team struggled to deploy and maintain ML models in production. Updates were slow, and the process did not scale as player behavior changed.
Our approach:
- Implemented Kubeflow pipelines for repeatable training and deployment - Integrated feature stores to standardize inputs and improve model reuse - Set up drift detection and automated model refresh based on player behavior
Results:
40% lower GPU costs within two months
12% increase in in-game revenue from improved personalization
Automated model updates with less operational overhead
Ready to embark on your MLOps journey? Talk to our experts for a free assessment.
Our Proven Approach
An MLOps consulting project at AppRecode usually consists of four distinct phases:
Tools and Technologies
The MLOps toolkit enables users to perform all stages of model development starting from training until they reach production readiness and subsequent updates. The automation of training and deployment and retraining processes becomes possible through Kubeflow and MLflow and TFX and SageMaker Pipelines and Vertex AI Pipelines which maintain workflow stability.
The system uses MLflow Tracking and Weights & Biases and DVC to track experiments and versions which enables researchers to reproduce their results. The deployment and serving process of KServe and BentoML and Seldon Core includes reliable model serving and traffic control and safe rollouts.
Monitoring and observability rely on Evidently AI plus Prometheus and Grafana to track model health, data quality, and drift signals. Infrastructure is provisioned with Kubernetes and cloud platforms such as AWS, Azure, and GCP, with Databricks ML used when a unified data and ML environment is required.
These tools keep model delivery predictable and auditable. The final stack is selected based on existing platforms, security requirements, and operational constraints.
Why Choose Us
Integrated Approach
Compliance
Scalability
Transparency
Proven Success
Ready to realise the benefits of MLOps? Talk to our experts and discover how we can help you scale safely.
Case Studies
FAQ
The service provides architecture design together with pipeline automation and versioning and monitoring and governance and cost optimization and training capabilities.
The main objective of DevOps involves delivering software applications together with infrastructure management. The process of data engineering creates dependable systems which handle data transmission. MLOps unites these fields to address specific obstacles which include model drift and reproducibility issues and the need for ongoing model retraining.
Yes. We integrate with current models and platforms, adding versioning, monitoring, and automation.
Absolutely. We implement compliance controls and audit trails required by healthcare, finance, and telecom regulations.
Yes. We serve clients across the USA and Europe, and our remote‑friendly team can engage regardless of location.
Rate Apprecode as Your Partner
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