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Applying Intelligent Search Capabilities to your Unstructured Documents

OVERVIEW • SETUP • CONCLUSIONS

Unstructured Document Search

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Context

Unstructured Document Search

Unstructured Document Search is a powerful and innovative information retrieval technique designed to uncover valuable insights from vast repositories of unorganized and diverse textual data. Unlike structured databases, unstructured documents, such as text files, emails, PDFs, and more, lack a predefined format or schema. This makes them challenging to search through using traditional keyword-based methods.

However, Unstructured Document Search leverages cutting-edge natural language processing (NLP) and machine learning technologies to make sense of this data chaos. By understanding the context, semantics, and relationships within unstructured text, it enables organizations and individuals to unlock a multitude of benefits and address various use cases.

Easy and fast setup. No complex infrastructure needed.

No need of specialized personnel.

Built-in semantic search and state-of-the-art LLM powered search.

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Unstructured Document Search

Document Search is like having a Google’s search bar for your documents, but with an additional AI capability that summarizes search results and answers questions in a interactive way.

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Document Search

Unstructured Document Search is provided under the Gen App Builder product. To setup Document Search you just need to provide it with an Google Cloud Storage bucket containing the .pdf, .txt or .json documents and import it to the app Data Store (source of data considered by Gen App Builder). You can also provide a BigQuery table or an API as a data source.

You can embed this search bar in your website or any internal UI system that supports html rendering.

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Technical Considerations Unstructured Document Search

Unstructured Document Search is powered by Google’s Gen App Builder out-of-the-box natural language understanding and semantic search.
It has out-of-the-box capabilities to understand synonyms, correct spellings, and auto-suggest searches without the need to implement complex natural language processing techniques.
The search summary is powered by Google’s Large Language Model PaLM.

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Key Takeaways

Google’s Gen App Builder allows you to quickly setup intelligent document search capabilities on you unstructured documents store without the need to know the complexities of Natural Language Processing or Machine Learning systems.