muzes is a young company that aims to make B2B sales as easy as buying a snack. Based in the UK, they are building one of the most innovative platforms on the market.
It is an amazing opportunity for Ulife to participate in this revolution through data, infrastructure and AI.
As an Ai solution provider, here at Ulife, we have created a safe space for muzes to take full access to the data available on their markets and built a streamlined process based on cloud architecture to fuel this mission.
Tags
- Generative AI
- Data collection
- Data infrastructure
- Content generation
- Azure platform
- Data analytic
The solution
We have provided the company with an architecture for automatic and regular data collection for their content needs and customer research.
The technologies used there are the following:
Airflow It is an open-source platform we have used to programmatically author, schedule, and monitor workflows at muzes. It allowed us to define tasks and dependencies as code, making building complex workflows with multiple steps easy. With that tool, we have easily monitored the progress of workflows and retried or re-run tasks if needed.
Azure Cloud Platform (AKS, Web services, Azure Containers Registry, Cosmos DB…)With the cloud platform, we have built the complete architecture to run the data collection tasks as well as use AI to make sense of this data and give them back to the end users.
PythonWith technologies like browser automation and web scrapping, web frameworks like fast API python have been of great help in the process of providing data to the end users.- SQL and NoSQL: For data storage
- DevOps automation processes (Github actions, …): Continuos delivery and integrations