Welcome to the era of Big Data where data-driven insights have the power to transform your business. You're about to discover the solution: a powerful, innovative and adaptive platform power packed with every feature you need for Search, Discovery & Analytics of your data.

We have named it 3RDi "Third Eye". It's the semantic search engine your enterprise needs to help you take action, boost revenues and cut costs! Powered by NLP and semantic search, it is designed for multidimensional information analysis and easy search relevancy management. Discover the comprehensive scalable platform for every challenge in search & text mining, from management and exploitation of unstructured content to deriving deeper actionable insights that boost your business.

Why choose 3RDi

3RDi isn't merely a search solution. It is a comprehensive stack of solutions for text mining, enterprise search, content integration, governance, analytics and much more. It is truly a one-stop solution for all your search and associated needs.

3RDi is designed as a suite of dynamic and pluggable components allowing enterprises to choose and customize only a selected set of components that is optimal for their business.

It's a highly secure and available solution with a backed up distributed and cloud environment.

There is nothing hidden. With 3RDi's open-source infrastructure you get the benefits of affordability, speed and collaboration while also enjoying flexibility and freedom.

To ensure a more relevant and useful experience for our customers from the Legal, Healthcare and Publishing businesses, 3RDi provides ready-to-use editions with domain-specific vocabularies and widgets.

Leverage your knowledge base by exploring our latest publications on Search, Discovery & Analytics

Scaling Apache Solr Hrishikesh KarambelkarOptimize your searches using high-performance enterprise search repositories with Apache Solr.
Scaling Big Data with Hadoop and Solr Hrishikesh KarambelkarBy combining Apache Hadoop and Solr, you can build super-efficient, high-speed enterprise search engines.
Scaling Big Data with Hadoop and Solr - Second Edition Hrishikesh KarambelkarUnderstand, design, build, and optimize your big data search engine with Hadoop and Apache Solr
Apache Solr: A practical approach! Dikshant ShahiFocuses on search concepts, challenges and explains different ways to achieve it in Solr.
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Well, let me start off with saying Healthcare is no stranger to changes. Challenges have always been there along the way and are constant, but so too have been the solutions.


The exponential growth of unstructured data is a reality and enterprises are facing a growing challenge of leveraging this unsurmountable amount of unstructured data for insights to drive business growth.


According to a study by the International Data Group (IDG), unstructured data is growing at an alarming rate of 62% per year. The same study also suggests that by 2022, close to 93% of all data in the digital world will be unstructured!!


The biggest challenge enterprises face when using a keyword based search platform is that a major portion of organizational data comprises of unstructured data. According to the Market Pulse Survey by SailPoint, over 71% of enterprises across the globe are not sure about how to manage unstructured data and the likely reason is that unstructured data is difficult to comprehend for a keyword based search tool.


This article explains how to implement SOLR "document level security" using Manifold Connector Framework. ManifoldCF is an open source framework for pulling content out of a repository and sending it on to targets such as SOLR via a plug-in style and connector-based architecture.


If you have multiple clients updating documents, it's really critical to ensure that a newer version of the document is never overwritten by the older version. To address this problem, what you need is concurrency control, which is the process of managing simultaneous updating of documents.


One of the lesser known but cool features of ReplicationHandler is support for index backup. You must have used ReplicationHandler in your project for replicating index from master to slave instances. If you want to take backup of index, you can do it as follows:


An ontology formally defines a common set of terms that are used to describe and represent a domain. An ontology is domain specific and it is used to describe and represent an area of knowledge.


Tesseract is probably the most accurate open source OCR engine available and with Apache Tika 1.7 you can now use the awesome Tesseract OCR parser within Tika! Solr 5.x has support for Tika 1.7. To try this out in Solr 5.2, the machine was configured accordingly…..


According to the official Docker website, "Docker is an open platform for developers and system admins to build, ship and run distributed applications." In simple words, it's one of the methods to run and deploy your software application. Docker allows you to create lightweight "virtual machines".


There are two ways to build docker image:

  1. Running an image, modifying and committing it. This requires to access a live container.
  2. Using a Docker file and building it


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  2. Take a tour, start experiencing

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