Business Impacts
Precise insights enhanced the decision-making process
Enabled real-time search on thousands of documents
Flexible search with human-like queries
Cost-effective and scalable
Customer Key Facts
- Country : US
- Size : $47 B
- Industry : Biopharmaceutical
Developed a system to efficiently search through vast repositories of documents
The innovation team of a global biopharmaceutical company required to mine knowledge insights from a large corpus of documents related to chemical processes and drug development generated by their internal R&D teams.
Challenges
- Continuously growing reports and process documents in varying formats
- Lack of real-time data analysis/visualization
- Semi-consistent manner of natural language querying
- No free text search capability
Technologies Used
BigQuery
Cloud Dataflow
Cloud Datastore
Custom Knowledge Graph Construction
Natural Language Classification
Spacy
Python
Solution
Quantiphi designed a Knowledge R&D Insights tool powered by Google Knowledge Graph/Base technology that allowed users to efficiently search and retrieve free text information and gain knowledge insights from the large corpus of biomedical documents generated by internal R&D teams.
Quantiphi built a cost effective and scalable model adapting Generative AI and Knowledge Graph techniques to classify, organize and link research content across different types of documents, with the goal of making this knowledge easily discoverable, consumable and insightful for the innovation teams
