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Healthcare dataset analytics platform

AI-powered dataset management solution reduced operational costs by 29%.

Client

Healthcare consulting company specializing in data analytics and support of the medical research community, set a goal of automating its dataset management process with AI technology.

Objective

The client was looking to leverage AI to automate dataset lookup and import, metadata harvesting, natural language queries execution, and other tasks. On top of that they decided to build and productize the web-based platform to offer this solution to other data analytics companies.

Solution

Achievion team started the project by analyzing all existing dataset variations and collecting platform requirements. Once all details were clarified, we designed scalable microservice-based solution architecture.

Then our engineering team developed and delivered the web-based platform using ACHIEVE methodology. The product includes the following features:

  • Search database using filters, keywords, and metadata variables
  • View and analyze search results
  • Compare datasets and variables
  • Admin interface for dataset management

We established the data collection mechanism to enable AI/ML models training and AI-powered capabilities implementation:

  • Intelligent data search
  • Automated metadata harvesting
  • Metadata variable summarization
  • Natural language search queries
  • Predictive analytics to determine potential gaps in the database and inform future dataset selection needs
  • Hyper-personalization of the search results according to individual user preferences

Result

The AI-powered dataset analytics platform delivered anticipated improvements in efficiency and cost-effectiveness to the client.

  • Reduced operational costs: through the automation of tasks such as dataset management, including lookup, import, metadata harvesting, and execution of natural language queries, the client witnessed a considerable decrease in operational costs, amounting to approximately 29%.

  • Increased productivity: this streamlined approach to dataset management translated into a 38% surge in productivity among data analytics teams. Consequently, they could allocate more time to strategic initiatives and support for medical research.

  • New revenue stream: opting for the development of a web-based platform proved to be a lucrative decision, as it paved the way for a new revenue stream for the client. The anticipated annual revenue growth is estimated at 31%.

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