Energy trading places high demands on speed, precision and reliable data. Prices can change in seconds, and the quality of a decision depends on the quality of the data it's based on.
The company already had its own trading framework. So the need wasn't another platform, but extra development capacity that could work directly in the existing solution.
The project included:
Instead of building a new system alongside the existing one, BCT worked directly in the company's setup.
A senior Python developer from BCT became part of the development environment and built on the existing trading framework.
The focus was on improving the way trading data was collected, structured and prepared for analysis - without disrupting the surrounding infrastructure.
The goal was simple: better access to data where it already existed, and a stronger basis for fast and reliable statistical analysis.
We replaced manual processes with automated data pipelines.
This reduced the need for manual handling and made data collection both faster and more consistent.
We built backend features and structured datasets that made it easier to analyze trading performance.
This gave the trading team faster access to the relevant data in a format they could work with right away.
Everything was developed directly in the client's existing Python-based trading framework.
Scalability, performance and stability were built in from the start, so the solution could work in an environment with high demands on both speed and operations.
All solutions were integrated directly into the company's existing IT environment.
No parallel systems and no temporary workarounds. Just better functionality in the solution the team was already working in.
By automating data collection and building directly on the existing framework, the company got a solution that was faster, more stable and better equipped to scale.
This made it possible to:
Most importantly, it gave a better basis for faster and more confident decisions in a market where both timing and data quality are crucial.
We helped Hafslund Kraft move from manual finance processes to a modern, cloud-based solution.
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