Glitni strengthens delivery capability in data science and MLOps

Glitni enters into a partnership with Telum -- the consultants who deliver results with artificial intelligence. By combining Glitni's expertise in data platforms and data engineering with Telum's experience in data science and MLOps, we can offer a comprehensive value chain for the development and operation of data and AI products.

Cross-functional collaboration is the key

We clearly see that breaking down technical and professional silos is the key to building better products and improving internal processes with data and AI. Both Glitni and Telum have consultants with extensive experience from mature companies and environments, where different disciplines work together to develop and operate full-stack data products used for critical decision support, innovative product development, and incremental process improvement.

Where Glitni has expertise in data platforms and data engineering, Telum has specialist competence in full-stack data science – including MLOps. The consultants at Telum have been instrumental in building the data science function at organisations such as Elkjop Nordic and Oda, and possess both deep domain knowledge and broad technical skills.

They have delivered and led business-critical projects in areas including product and content recommendations, search, forecasting, supply chain optimisation, customer segmentation, pricing, image processing and text processing, and have implemented MLOps infrastructure to efficiently develop and operate these projects.

Together, Glitni and Telum can offer both the implementation of platform capabilities and the development of data and AI products, whether it involves bespoke solutions with high complexity or seamless integrations with off-the-shelf products.

The Telum team

Kjetil Amdal-Saevik | Data science & MLOps

Kjetil is an experienced data science leader, data scientist and MLOps engineer with a background from organisations including Elkjop Nordic and Oda. He has been involved in the development of commercially relevant and technically leading machine learning solutions since 2014, and has extensive experience in scaling up and putting data science on the agenda in both established companies and start-ups.

Aleksander Wang-Hansen | Data science

Aleksander is an experienced data scientist and team leader with a background from organisations including Oda. He is a former elite athlete and an effective problem solver with a solid background in mathematics, statistics and machine learning. He has significant practical experience in building highly business-critical machine learning and optimisation solutions, as well as providing strategic advisory services and training.

Jens Fredrik Skogstrom, PhD | Data science

Jens Fredrik is an experienced data science leader, data scientist and analyst with a background from organisations including Statistics Norway (SSB), Menon Economics and Oda. He is exceptionally strong at turning theory into commercial results, and has extensive experience in delivering and leading machine learning and analytics projects to improve both end-user products and internal workflows across various companies.

Examples of AI deliveries the team has experience with

• Bespoke machine learning solutions for forecasting that can be combined with human judgement, for use in areas such as workforce planning and procurement.
• Optimisation and simulation solutions for production and logistics – often combined with machine learning models – for efficiency improvements across various stages of the supply chain.
• Predictive customer segmentation models for targeted marketing and product improvement.
• Product and content recommendation systems based on both structured and unstructured (text, image, video, audio) data.
• Search solutions for all forms of content, using language models for optimised, self-improving indexing and querying.
• Lean, flexible MLOps setup that combines development and deployment locally and in the cloud (Azure and/or Google Cloud Platform), for data science teams that want to be highly productive and deliver operationally reliable solutions.