14. Summary

Summary

Influenced by internet search, people are no longer satisfied with ranked search results from keyword queries. They want to type in full questions and get answers. They expect search applications to support natural language queries, featured snippets and even generative answers. Traditional search is not enough. Discovery brings together all the components you need to provide your users with the advanced search experience they now expect.  

Modern cloud-native architecture 

Discovery was born in the cloud. We are building a cloud-native architecture that exploits the flexibility and resilience of cloud computing. And enables clients to run scalable, efficient, and secure search applications in modern dynamic environments such as public, private and hybrid clouds. 

 Dynamic data connectors 

Data connectors are required to gain access to content sources such as file systems, databases and websites and feed data into Discovery. Discovery’s data connectors ingest data in a scalable and efficient manner while honoring access controls. Plus, they monitor the data source for additions and deletions and process them as they occur. 

 Intelligent content processing 

Poor quality data, especially metadata, can have a detrimental impact on search performance. Discovery uses intelligent content processing pipelines as it ingests data to refine and optimize it for retrieval. Content is cleansed, enhanced, and normalized and can be further enriched via services for entity extraction, metadata augmentation, tagging and classification. 

 AI-Powered 

At its core search is about understanding language and Discovery takes full advantage of AI technologies such as Generative AI and Vector Search. These AI technologies enable users to search in a way that feels natural and surface relevant results. For example, vector similarity search uses Machine Learning to provide a much more refined way to find content with subtle nuances and meanings. And featured snippets use a combination of AI technologies to extract a specific piece of text from a document that best answers a user’s search request.  

 Integrated Knowledge Graph 

A knowledge graph is a database of entities – i.e., people, places, and events – and the relationships between them. As such, they have proved enormously powerful in question-answer systems. Discovery uses knowledge graph technology to provide direct answers to factual questions. 

 API and Versatile UI 

The goal of any search application is to serve the users’ needs quickly and efficiently. Discovery includes a powerful API that developers can use to create a fully personalized search experience. Sophisticated query parsing, NLP and other AI services are deployed to help understand the intent of a user’s search request. Security is included in this API to ensure users are served only results they are allowed to see. Discovery also includes a complete React based Search User Interface that clients can deploy with minimal development effort.  

 Elevate Open-Source Search 

Discovery has been designed to enhance traditional open-source search engines by integrating them with knowledge graph and AI technologies to provide advanced search features. You can choose to augment your existing open-source search engine with Discovery or leverage the complete platform to meet the requirements of your organization.  

 Achieve Cost Efficiencies 

Discovery can help you build a better search application for your workplace, website, or support portal. It can improve the embedded search experience for your information service or software product. Combining Discovery with top open-source technologies results in a cost-efficient means to achieve functionality on par with top commercial cognitive search solutions. 

 You can choose to augment your existing open-source search engine with Discovery or leverage the complete platform to meet the requirements of your organization. Either way, Pureinsights can help you assess, design, and develop your search application and provide on-going support and maintenance.