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Data Analysts: Enhancing Analytics with AI

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Our customer is an innovative SaaS platform for analytics. It is a fast-growing startup based in the USA. Its vision is to take the data intelligence experience to the next level by ​​​​​leveraging big data technologies and predictive analytics. They have many customers across different industries who use our product to get insights from their data daily.

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The Business and Technical Challenges:

Backend of customer's platform developed with Scala. 

Our engineers worked on a solution that would allow platform users to easily manage data, make queries, visualise graphs, create forecasts based on existing data, etc:

  • рarse a user request in human language with business terms;

  • form an appropriate query to the database; 

  • display the results of the query execution from the database in dashboards;

  • generate SQL from the user's text input;

  • visualise the results.

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The Solution:

Our team decided not to use the previous Rasa neural model. Instead, we decided to rewrite the processing of user requests so that they are only in the code: the user's request is processed using AI models from OpenAI.

 

The Tech Stack Used in the Project:

  • Scala, Python

  • OpenAI API, LangChain

  • Chroma (with VectorDB)

  • RAG pattern

 

The Result:

Our team of engineers improved the platform as follows:

  • created tools with which platform users can independently and quickly collect their data and visualise it in the required context;

  • added new analytics capabilities;

  • facilitated the work of data analysts in data collection and forecasting.

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The Client:

Industry: Big Data

Location: USA

Team size: 2 Data Engineers

Cooperation:  2 years 3 months

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