We help organisations implement MLOps best practices to streamline the development, deployment and ongoing management of machine learning models and pipelines at scale.
By introducing MLOps processes and leveraging CI/CD principles, we enable you to rapidly build, test, release and monitor performant and reproducible machine learning systems.
Our full-lifecycle services provide the people, processes and platforms needed to maximise return on ML investments whilst minimising technical debt and operational overheads.
We start every engagement by gaining a thorough understanding of your challenges, ML objectives and constraints. Our data and DevOps engineers then map out an MLOps strategy focused on automating and optimising your model development lifecycle.
We help implement MLOps best practices including CI/CD pipelines to enable automated building, testing and deployment of ML models, data and components. With rigorous testing validating models prior to release, and proactive monitoring enabling ongoing enhancement.
With MLOps, models can be rapidly packaged, delivered and deployed in repeatable, reusable configurations. We ensure you have the visibility and control needed to address concerns around regulatory compliance, reproducibility and technical debt.
Overall delivering faster development cycles, quicker time to value, lower costs and strategic scalability, empowering organisations to proactively build, manage and optimise intelligent systems.
Commodity contracts and services supported for one of the world's largest agricultural organisations
Funding allocation managed each year for the nation’s largest funder of health and care research
Pupils tracked across 12,000 UK wide schools
Annual sales supported through a knowledge management platform for a global manufacturer
Implementing processes to rapidly develop, test, deploy, release and manage trusted machine learning solutions.
Offering comprehensive solutions for managing the entire lifecycle of machine learning models, including development, deployment, monitoring, and iteration.
Implementing CI/CD pipelines tailored for machine learning projects, enabling automated testing, integration, and deployment of ML models.
Providing tools and services for monitoring the performance and health of deployed models in production, including version control and rollback capabilities.
Delivering ML solutions using cloud services covering Azure, AWS and Google Cloud.
From AI powered WhatsApp chatbots, to image recognition systems and planning optimisation tools.
Northern Trains is a train operating company that provides services across the North of England. With over 500 calling stations, the company connects major cities like Manchester, Leeds and Newcastle. The company plays a crucial role in facilitating transportation and commuting for thousands of passengers every day.
A UK-based large food manufacturer, established for over 100 years, providing products as part of a healthy, balanced diet, through a range of products to suit all meal occasions, lifestyles and tastes.
A global leading provider of infection prevention and other procedural products and services, focused primarily on healthcare, pharmaceutical and medical device customers, with more than 17,000 associates worldwide.
A nationwide energy provider who specialises in supplying energy to a wide range of businesses with a UK-based team, from SMEs through to large national chains, knowing what energy challenges businesses face and how to support them.
A no-code work management platform that enables anyone to replace spreadsheets with custom applications to track and manage work. From marketing professionals, to sales teams, HR managers and agencies of all kinds, empowering people across all industries to innovate by developing the software that they need.
From start to finish the working relationship between Audacia’s team and ours was productive from the iterative development approach, meaning we worked in shorter time frames but increased levels of communication to ensure all updates were reviewed quicker. Audacia’s end platform delivered on all aspects.
- Sarah Thorp, The National Institute of Health Research (NIHR)
Insights on the latest industry developments and technology advancements within AI & machine learning.
In today’s fast-paced technological environment, AI and machine learning are being adopted for innovation and efficiency in various industries. This article covers MLOps best practices and the critical role of tools and technologies in facilitating efficient ML lifecycle management.
We explore everything everything from the fundamental concepts of AI and ML, approaches and use cases, to industry examples of implementations across data, vision and language.
Software development company, Audacia, has partnered with Northern, one of the UK's largest rail operators, to launch an innovative new AI-powered chatbot on WhatsApp
This article aims to assess the strengths, challenges, and considerations of public, private, and hybrid cloud approaches for AI integration, empowering IT Directors and CIOs to make informed decisions that align with their organisation's unique requirements.
As a first step in the process, we offer a free consultation around your current setup. We'll discuss your challenges and goals and see whether we could be a good fit for delivery.