Mon – Fri: 10:00 – 18:30
Mon – Fri: 10:00 – 18:30
Service · AI Cloud Services and MLOps
Xister Providing end-to-end machine learning lifecycle management to build, deploy and maintain scalable and robust machine learning solutions.
A trusted partner
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.
Delivering end-to-end MLOps
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 supported through trading platforms we’ve built
Funding allocation managed annually on platforms we’ve delivered
Pupils tracked across thousands of UK-wide schools
Annual sales supported through enterprise knowledge platforms
End-to-end delivery
01
Upgrading, re-platforming or replacing systems that no longer serve the business — without disrupting the people who depend on them.
02
Designing and building user-focused products and new digital services, integrated cleanly with the systems you already run.
03
Extending your in-house engineering and QA capacity with senior specialists who plug into your roadmap and ship at pace.
How we work
Implementing processes to rapidly develop, test, deploy, release and manage trusted machine learning solutions.
01
Offering comprehensive solutions for managing the entire lifecycle of machine learning models, including development, deployment, monitoring, and iteration.
02
Implementing CI/CD pipelines tailored for machine learning projects, enabling automated testing, integration, and deployment of ML models.
03
Providing tools and services for monitoring the performance and health of deployed models in production, including version control and rollback capabilities.
Technologies
Delivering ML solutions using cloud services covering Azure, AWS and Google Cloud.
Industries
From AI powered WhatsApp chatbots, to image recognition systems and planning optimisation tools.
From start to finish the working relationship between Xister'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. Xister's end platform delivered on all aspects.
