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We are a boutique provider specialising in data analytics and data intensive proof-of-concept and pilot solutions in the digital realm.
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Technical Assistant using Generative AI
CLIENT:
Global Industrial Manufacturer, headquarters in Sweden
PROBLEM:
A global industrial manufacturer headquartered in Sweden offers industrial materials to manufacturers worldwide. They built a website for customers to search and find these materials but wanted to provide even easier access to their technical support material. Additionally, the support material was mostly in English, while customers might prefer other languages.
SOLUTION:
As part of a project team, we implemented an ETL pipeline to extract the client's technical support documents, chunk them, and store them in a vector database. We then developed a custom chat interface using generative AI, enabling it to retrieve information from the database and converse with customers. An A/B test was conducted on the website to compare the performance of the generative AI support tool against the existing implementation where users had to find information by clicking and navigating.
Operational Dashboard for a Digital Service
CLIENT:
A wholesale company for medical products
PROBLEM:
A wholesale company for medical products develops and provides digital services to their customers. The applications serve different customer groups with varying needs, such as making large purchases, ordering in smaller batches, or simply accessing product information. Business stakeholders and application designers lacked visibility into which customer groups were using which apps and what functions of the apps were being used.
SOLUTION:
Working closely with the client's stakeholders, we gathered key decisions they wanted to make based on analytics data and formulated requirements for the reporting. We set up data collection of user events to Google Cloud BigQuery. We created a simplified reporting layer on the event data and developed a dynamic dashboard for reporting. The dashboard enabled segmenting metrics by customer group or application boundary, providing valuable insights for stakeholders and designers.
Dynamic Pricing in B2B Ecommerce
CLIENT:
B2B Ecommerce company, Finland
PROBLEM:
A B2B Ecommerce vendor needed to show different prices to different customers based on rules from their ERP system. Their existing ecommerce platform did not support differentiated pricing automatically.
SOLUTION:
Our company implemented a solution using AWS services to fetch product prices and rules from the ERP whenever there was a change. This data was turned into an API capable of calculating prices based on customer ID. The API was integrated into the ecommerce system, overriding default prices for logged-in customers.
Complex Data Warehousing
CLIENT:
Central organization in sports
PROBLEM:
A central organization in sports needed to create a data warehouse to store data from over a hundred of different sources and provide a combined view of key metrics. The data sources included event data, sales rows, and pre-aggregated data. The client faced coordination challenges as some data sources were not under their direct control. Additionally, they required a robust reporting layer to share insights with stakeholders who were not directly part of the client's organization.
SOLUTION:
We implemented a custom ETL stack using AWS CloudFormation and Lambda functions, enabling easy updates to the pipeline as new data sources were added during the project. This approach also allowed for cost-effective execution and re-use of configurations for different data sources. We developed a processing layer that combined data from various sources into a single reporting layer and enabled the sharing of key metrics with external stakeholders through an innovative approach.
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