Automatic unstructured PDF ingestion on GCP

The scope of this session is to show how it is possible to create a Question Answering agent on GCP starting from complex documents, like technical handbooks. This will be done by using the following passages:

1. Document Segmentation
Semantic structures (like title, sections, tables...) will be inferred with State-of-the-Art models.

2. Optical Character Recognition (OCR)
Google OCR will be applied to the previously-determined structures in order to determine their content.

3. Vectorization
The text will be saved in a vector store in order to allow a fast information retrieval.

4. Large Language Model (LLM) Connection
The vector store will be connected to an LLM that will be used to provide the user with suitable answers for his/her questions.

This project will showcase the capabilities of State-of-the-Art models and technologies in the field of Generative AI.

Speaker Bio:

Bachelor in Statistics, Master Degree in Data Science, in Ennova-Research since 2021 working on many AI related projects