Machine Learning Consulting & ML OPS

Critical insights to elevate your business data operations

We help ensure that your machine-learning projects are scalable, reliable, reproducible, and maintainable over time

Looking to automate your business? Companies wanting to utilise AI and Machine Learning face significant obstacles. There is a prominent gap in the talent market for the skills, knowledge and resources to make intelligent, fit-for-purpose solutions.

One51 carries a wealth of expertise in machine learning consulting, with evidence-backed insights that help businesses navigate issues to help make these innovations happen.

What is MLOps?

Investing in Machine Learning Operations means you can expect better overall performance and efficiency from your future machine learning models. Machine Learning Operations (MLOps) is a discipline built on a set of practices and techniques that aim to streamline and automate the deployment, management, and monitoring of machine learning models in production environments.

MLOps combines the principles and best practices of DevOps (Development Operations) with the specific challenges and requirements of machine learning to reach this goal.

Benefits of Implementing MLOps

Accelerated model deployment
Improved model performance and reliability
Enhanced collaboration and efficiency
Scalability and cost optimisation
Support compliance and governance

Who will benefit the most from an MLOps implementation:

Data Scientists and Machine Learning Engineers

MLOps lets data scientists and machine learning engineers streamline their workflow and automate repetitive tasks. It provides them with tools and frameworks to deliver models more efficiently and frees up time to focus more on model building and experimentation.

Software Development Teams

MLOPs help bridge the gap between software engineering and machine learning for software developers. This enables smoother integration of ML models into software applications.

IT Operations and Infrastructure Teams

MLOps gives IT Operations and Infrastructure teams orchestration capabilities that make it easier to deploy and scale machine learning models. MLOps makes it easier for these teams to efficiently provision and manage resources with tools such as containerisation technologies, cloud platforms and infrastructure-as-code.

Business Stakeholders

MLOps helps business stakeholders by fast-tracking the deployment of machine learning models and improving their reliability and performance. This helps significantly cut the time to market for new AI-drive applications.

End Users and Customers

Machine Learning Operations help enhance the user experience for customers. Creating faster deployment of machine learning solutions that are reliable and accurate in performance.

Properly implementing MLOps helps improve the overall performance of your data and IT teams, letting these professionals focus on their work and less on administration.

What our MLOps engineers offer

1. Valuable expertise and experience to guide your MLOps implementations

MLOps is a complex and specialised field that requires a deep understanding of machine learning, software engineering, and infrastructure management. If your organisation lacks the necessary expertise or experience in implementing MLOps, One51 can provide valuable guidance and best practices based on our experience working on similar projects.

We bring domain-specific knowledge and insights to help you navigate the implementation challenges effectively.

2. Accelerated implementation through ready-to-use documentation

One51 can help you accelerate the MLOps implementation process. Our expertise and experience can help streamline the implementation by providing ready-to-use frameworks, tools, and methodologies. We will guide your team in making informed decisions, avoiding common pitfalls, and ensuring a faster and more efficient implementation.

3. We can fill in skill gaps

Our consultants can complement your in-house team and fill skill gaps that slow down MLOps implementations. We will bring our specialised skills and knowledge that may need to be more readily available within your organisation. This allows your team to learn from our consultants and gain new skills, enabling a smoother transition towards self-sufficiency in MLOps practices.

4. An unbiased perspective on your MLOps implementation

We will objectively evaluate your existing processes, infrastructure, and workflows, identifying improvement areas and suggesting tailored solutions.

5. Flexible short-term engagement

We are flexible to support you during specific phases or tasks of the MLOps implementation. This allows you to leverage our expertise on demand without committing to long-term contracts.

Once the implementation is complete, your team can continue managing and maintaining MLOps practices internally.

Ongoing Support for MLOps Implementations

Organisations require ongoing support after an MLOps implementation to ensure the continued reliability, scalability and performance of their machine-learning operations.

We recommend all our clients plan to establish a support team after the project or consider allocating resources for professional assistance.

Monitoring and performance management to track and analyse the performance of ML models and possible anomalies.
Model retraining and iteration periodically to adapt to changing data patterns, business requirements, and environmental shifts.
Infrastructure maintenance with regular updates, security patches, and performance optimisations to maintain a stable and efficient infrastructure around machine learning models.
Infrastructure scaling with resource allocation and new changes to align with growth
Data governance to ensure data quality, privacy and security
Data management through monitoring data sources (through solutions like visual reporting) and managing pipelines to ensure compliance with best practices in data governance
Up-to-date documentation and knowledge management to maintain knowledge bases and run-books to onboard new members, troubleshoot problems and ensure continuity in MLOps processes in your team.
User support and training to address user queries, provide guidance on using machine learning models, and troubleshoot issues.
Continuous improvement and innovation to stay updated with the latest advancements in machine learning technologies, explore new algorithms or frameworks, and identify new opportunities to optimise and enhance existing MLOps processes.

Complete Machine Learning Solutions for Businesses

Our MLOps and ML engineers at One51 are dedicated to providing holistic solutions to enable companies to deploy machine learning models for their businesses.

If you’re looking for professional assistance, we are able to offer work through a range of arrangements: short-term contracts, complete projects, optimisation and health checks.

Contact us today to book a machine learning consultation and get a solution. At One51 Consulting, we’re dedicated to helping elevate the data platforms of businesses.