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MLOps Services
Streamline machine learning workflows with our tailored MLOps services. The Requestum team automates model development, simplifies deployment, and ensures consistent operations by combining machine learning practices with proven DevOps approaches.
What MLOps Is and Why It Matters
MLOps (Machine Learning Operations) is a set of practices that streamline the development, deployment, and management of machine learning models, making them scalable, reliable, and easier to maintain. With the global MLOps market projected to reach $19.55B by 2032, more businesses are adopting MLOps as a service to gain better control and consistency across their ML workflows. At Requestum, we provide end-to-end MLOps development services, helping to turn your ML initiatives into robust, production-ready systems.
The Value of MLOps Services for Businesses
Faster model deployment
MLOps streamlines testing, validation, and deployment workflows, reducing the time it takes to bring models into production and start delivering real business value.
Improved reliability and monitoring
With automated testing, version control, and continuous monitoring, MLOps ensure that your ML models perform consistently in production and adapt to changing data.
Scalability for growing demands
MLOps services make it easier to manage and scale complex ML models and workflows, supporting growing data volumes and business needs.
Continuous model optimization
MLOps solutions enable automated retraining and performance tracking, keeping your models accurate, relevant, and aligned with changing business needs.
MLOps Development Services We Provide
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Model development & experimentation
Model development & experimentation
Requestum builds and trains machine learning models using proven tools and frameworks. We support various modeling techniques, hyperparameter tuning, and evaluation to streamline experimentation and improve results.
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Strategic MLOps consulting
Strategic MLOpsconsulting
Within MLOps consulting services, our team of experts helps you design a tailored MLOps strategy, offering practical guidance for successful model deployment, lifecycle management, and operational stability.
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Model deployment automation
Model deployment automation
We implement automated deployment pipelines to eliminate manual steps, reduce errors, and ensure fast, repeatable, and consistent delivery of machine learning models across any production environment.
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Real-time monitoring & retraining
Real-time monitoring & retraining
Our specialists set up systems to track model performance in real time, detect drift, and automatically retrain models when needed. This ensures your models remain accurate and aligned with evolving data.
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Model explainability and bias detection
Model explainability and bias detection
The Requestum team applies trusted tools and methods to interpret ML predictions and expose decision logic, helping detect and mitigate bias, improve transparency, and ensure regulatory compliance and user trust.
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End-to-end MLOps platform integration
End-to-end MLOps platform integration
Our team integrates MLOps tools into a cohesive platform, covering data preparation, model training, deployment, and monitoring to streamline the full ML lifecycle and increase operational efficiency.
Model development & experimentation
Requestum builds and trains machine learning models using proven tools and frameworks. We support various modeling techniques, hyperparameter tuning, and evaluation to streamline experimentation and improve results.
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Model development & experimentation
Requestum builds and trains machine learning models using proven tools and frameworks. We support various modeling techniques, hyperparameter tuning, and evaluation to streamline experimentation and improve results.
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Strategic MLOps consulting
Within MLOps consulting services, our team of experts helps you design a tailored MLOps strategy, offering practical guidance for successful model deployment, lifecycle management, and operational stability.
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Model deployment automation
We implement automated deployment pipelines to eliminate manual steps, reduce errors, and ensure fast, repeatable, and consistent delivery of machine learning models across any production environment.
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Real-time monitoring & retraining
Our specialists set up systems to track model performance in real time, detect drift, and automatically retrain models when needed. This ensures your models remain accurate and aligned with evolving data.
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Model explainability and bias detection
The Requestum team applies trusted tools and methods to interpret ML predictions and expose decision logic, helping detect and mitigate bias, improve transparency, and ensure regulatory compliance and user trust.
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End-to-end MLOps platform integration
Our team integrates MLOps tools into a cohesive platform, covering data preparation, model training, deployment, and monitoring to streamline the full ML lifecycle and increase operational efficiency.
Why Choose Requestum for MLOps Services
Proven AI expertise
We have a strong foundation in advanced AI disciplines, including machine learning, deep learning, computer vision, and natural language processing. This diverse expertise enables us to offer MLOps solutions that are not only technically sound but also solve complex, real-world business challenges.
Business-driven approach
We understand that every organization has its unique goals. That’s why we tailor our solutions to align directly with your business objectives. Whether it's optimizing workflows, reducing costs, or accelerating innovation, we focus on delivering measurable outcomes that make AI a strategic advantage.
Focus on long-term partnership
Choosing Requestum means gaining a dedicated technology partner who supports you beyond the initial deployment. We build adaptable solutions that evolve with your needs. Our commitment to long-term collaboration ensures your investment continues to deliver value as your business grows.
Client-centered collaboration
We believe the best results come from close collaboration and open communication. That’s why we prioritize transparency and active involvement at every stage of the project. Our client-first approach builds lasting trust and ensures we’re always aligned with your vision and goals.
Our Case Studies
AI Solution for Analyzing & Streaming Casino Card Games in Real-Time
We implemented a solution that proved to be an invaluable asset for our client. It provides casino owners with critical insights into table load, employee behavior, and potential security vulnerabilities. The software not only enhances security measures but also equips our client with a competitive edge, facilitating more efficient casino operations through improved analysis of games, players, and staff.
Demand Forecasting Solution for Transportation Services
By blending advanced machine learning, geospatial analysis, and real-time data integration, this solution improved daily operations and allowed transport companies to respond to fluctuating demand.
Detection of Cars on Overhead Images
The primary aim of this project was to calculate the density of cars in a chosen region. This analysis was crucial for understanding traffic patterns, aiding urban planning, and developing smart city initiatives.
What our customers say
Discover testimonials from our clients and learn why they trust us.
What our customers say
Discover testimonials from our clients and learn why they trust us.
James Hodson
CEO, MySyla
Requestum works more efficiently during a war than most other teams work in peacetime. The quality of development work is excellent on all fronts. Despite setbacks with the team needing to move around the country to stay safe, air raid sirens, and Internet outages, the team has never missed a deadline or gone a day without finding a way to communicate. Requestum genuinely cared about making sure the final product was exactly what was needed. The team improved the features in ways that we could never have come up with ourselves. They obviously enjoy working together, and have created an excellent team spirit and work ethos.
Danny van de Griend
CEO, Cecil Alliance
Requestum was always accessible and ready to discuss new ideas. Every suggestion that i have made during the project was carefully considered, and went through feasibility pipeline which worked perfectly for my platform.
VERIFIED
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Ben Clink
Head of Customer & Digital, South Sydney Rabbitohs
I can confidently call Requestum a reliable partner who delivered an easy-to-use, feature-rich app on time and within budget. The team worked collaboratively, accommodated all requests and scope changes, and communicated effectively throughout the project. They went the extra mile to understand and respond to the requirements.
GianBruno Torrano
Vice President, Soft-net Sp. Z o.o.
The team is readily available and regularly checks in. Their responsive nature sets them apart and supplements continued engagement. Requestum has facilitated a positive customer experience by understanding the requirements and successfully implementing a number of complex backend functionalities.
Ruairidh Galbraith
Digital project manager, Uncommon Knowledge
The team at Requestum is very friendly, efficient and professional. We have worked with them on more than one occasion and are very pleased with the quality of service. So far we’ve made back the money that we spent in less than eight months of launching.
Latest Insights
Frequently Asked Question
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Why should I invest in MLOps ?
MLOps makes it possible to deploy, monitor, and maintain machine learning models at scale. It reduces operational risks, improves reliability, and shortens time-to-value, ensuring your ML initiatives are efficient, cost-effective, and aligned with business goals.
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Can MLOps development services help me improve the accuracy of my machine learning models?
Yes. MLOps supports continuous monitoring and retraining, helping your models stay accurate as data evolves. It also speeds up experimentation, enabling faster iterations and improvements based on real-world performance feedback.
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What is the typical timeline for deploying an MLOps solution?
Timelines vary based on project complexity, data quality, and integration needs. A basic ML solution may take 4–8 weeks, while more complex models with MLOps pipelines, deployment, and monitoring can take 8–16 weeks or more.
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What steps are involved in your MLOps consulting services?
Our MLOps consulting includes an initial assessment, infrastructure and toolchain planning, pipeline design, automation setup, model deployment strategy, monitoring configuration, and knowledge transfer. The process is tailored to your specific use case and tech stack.
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How do I choose the right vendor for MLOps services?
Look for a vendor with hands-on experience in deploying ML models at scale, a clear understanding of both data science and DevOps, and a track record of building automated, secure, and maintainable ML pipelines.
Our contacts
We are committed to ensure quality in detail and provide meaningful impact for customers’ business and audience.
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UA Sales Office:
sales@requestum.com -
HR Team:
talents@requestum.com -
Estonia
15551, Harju maakond, Tallinn, Lasnamäe linnaosa, Sepapaja tn 6
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Ukraine
61000, 7/9 Svobody street, Kharkiv
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Switzerland
6313, Seminarstrasse, 5, Menzingen