Our client, a leading publisher needed to make their data easily accessible to users via an easy-to-use search function. For this, they needed a robust, self-learning information retrieval platform which would ingest over 300 data sources and make it available in a user-friendly manner.


Infosys leveraged its AI platform NIA, to develop a stable architecture design and implemented an Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) compliant data harvester. This enabled the ingestion of data at scale using a variety of open source and AWS tools. Search functionality was enhanced to include advanced NLP and machine learning techniques, along with automated ‘type-ahead’ features.



Spark-based ETL framework ingested data containers in just 2.8 seconds

Systematic approach to search quality assessments

Search functionality improved through NLP and machine learning

Awarded Best Search Project by Information Retrieval Specialists Group

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