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Comprehensive Search Engine

Intranet Search at its Best

A smart search function without compromise. All content can be searched for within seconds- regardless of quantity, format, or storage location.

INTRANET SEARCH ENGINE WITH ARTIFICIAL INTELLIGENCE

Find instead of search within seconds thanks to AI

An elementary component of the narvika intranet solution is a genuine enterprise search technology that makes all content immediately findable, regardless of the format or location in which it was stored. A wide range of filter options are available to help you find what you are looking for quickly and efficiently, even with millions of documents. The direct preview gives you an immediate overview of all further details without leaving your intranet. The integrated expert search automatically displays the right contact person for the relevant search results.

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Leading search technology

INTERGATOR Smart Search

narvika relies on the established and leading enterprise search technology intergator, the company interface projects GmbH from Dresden. With customers all over the world from a wide variety of industries, including many German authorities, this technology is group-proven and, in addition to all requirements for a search engine, also meets the highest data protection guidelines.

Intergator homepage Customer list

Cloud or on-premises

Data Protection made in Germany

Data protection and data security are elementary challenges in search technology. A search engine has access to all information and must ensure the correct interpretation of authorisations at different levels so that each employee can only find and view the appropriately authorised content. The authorisations of the respective source system (e.g. emails) are taken into account and precisely processed during the search query. With the knowledge and experience from over 10 years of development work and countless search projects, you are on the safe side with the narvika integrated Smart Search. If you wish, your intranet can also be implemented in compliance with DIN EN ISO 9001:2015

Machine Learning

Find even more precisely with artificial intelligence

With the help of machine learning and artificial intelligence processes, the narvika intranet can be made even better and more efficient. In particular, projects based on the integrated Smart Search have already been successfully implemented in the area of the classification of texts (e.g. emails) and autonomous image recognition. The aim is usually to automate the manual processing of large amounts of data (e.g. support inquiries) to a certain degree or completely. AI-supported functions are highly topic and project dependent, so this service is only part of narvika enterprise. You can start almost immediately with the very affordable narvika fixed price, and take advantage of the offer to evaluate deeper AI-supported optimizations at a later point in time.

narvika Search Engine

Intranet search: popular features and use cases

Expert Finder: Find the Right Contact Person.

With the narvika Expert Finder, the right contact person for certain topics and competencies is automatically displayed in the hit list.

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Extended Search Function & Auto-Suggestion

Search results are sorted according to various factors so that you always find the most relevant content first. With large amounts of data and millions of hits, the results can also be narrowed down more precisely using the extended search function.

  • Not only the document title is taken into account, but all other meta-information of a document is also interpreted in addition to the full-text analysis and can be searched separately
  • Customer-specific synonym lists can be stored in order to to make your own abbreviations or industry-specific terms easier to find
  • Geo-area search allows you to search for documents in the area of a geo-coordinate (GPS position, postcode, address, etc)
  • Auto-suggestion suggests similar terms or combinations of terms while you are entering the search.
Strong Filters, Perspectives, and Facets

An integral part of the narvika search is the many filter options and related functions to find what you are looking for as quickly as possible, even with very large amounts of data. The filters are generated automatically from the existing meta information and adapt dynamically to the respective search query so that the only filters available lead to actual hits.

Standardised filter options:

  • Date and period e.g. December 2019
  • Data source and storage location (such as file server)
  • Document type (such as Presentation, PPT, etc)
  • Place of creation, e.g. Hamburg
  • Creator or editor (for example, created by Max Mustermann)
  • Language (automatic language detection)
  • Category (such as email)
  • Colour coding
  • Geo-coordinates.

In addition, individual filters (e.g. according to specific customer numbers, etc.) can be implemented.

Compensate for Poor Data Quality and Remove Duplicates

We know from everyday project work that the data quality of internal content can vary greatly. Duplicate and very similar versions of the same content filed in different places are the order of the day and make it difficult to find relevant and current information.

There are many ways to effectively compensate for these disadvantages without having to manually adapt or delete existing content. Such as:

  • Manipulation of the various ranking factors by power users and admins
  • Blacklisting of obviously incorrect, incomplete, or undesired content
  • Boosting of new content or data of special quality (e.g. official instructions, news, etc.)
  • Duplicate report for deleting redundant data
  • Subsequent keywording of the content within narvika
  • Comment function of the content within narvika.
Remember, Share, and Export Search Results

The strength of the narvika search engine is the relevant listing of all documents on a term or combination of terms regardless of where this information is stored. These hit lists can of course be very long and usually, only the first results are decisive.

But there are also valuable use cases that are based on this function:

  • You can remember certain search queries and share them with other employees. For example, if you can only find certain documents after narrowing down the filter further and you are looking for the relevant information again and again. Say, you're looking for all emails from a specific customer on a certain topic in the last 2 months. You can save this search process (share if necessary) and you will also receive all new emails with these criteria in the future with just one click.
  • Hit lists and corresponding documents can be exported with the takeouts. Example: All PDF documents for a specific process, regardless of where the data is stored. More details under the narvika Takeouts.

narvika self-learning search

AI-Search: More features and use cases

Find information even though there is no search term

You are looking for a specific term, but the document you want only describes that word or combination of words. Exact keyword-based search engines do not provide any results here. A new approach to solving this problem is the use of machine learning methods. Here, a trained computer independently classifies and categorizes content and data and locates them within a multidimensional vector space. If you search for a term, the search returns not only the exact hits but also the hits that are relevant to the content - regardless of whether the term appears in it or not. The exact match is supplemented by a conceptual search.

Automatic Image Recognition

Adding keywords to images manually is a tiresome endeavor and is often neglected in the hectic everyday working life. Here, too, methods based on machine learning can help and automatically recognize the content of the image. With this knowledge, appropriate keywords can be automated or the next process step can be initiated immediately. Images are classified and categorized here based on pure image information. Dermatologists are already using similar methods for the early detection of skin cancer, but practical examples are also available in a corporate context:

  • Spare parts detection: The defective part is photographed and automatically compared with the spare parts database. The corresponding reorder can be suggested or triggered directly
  • Damage management: Images of damaged items, packages, or with incomplete references can be automatically pre-sorted and categorized.
  • Similarity search: Recommendation function often used in e-commerce for similar products or services based on photos.
Foreign Language Interpretation without Translation

With machine learning methods, the computer recognizes the actual content of the document and classifies it accordingly based on previous experience. This is done separately from the individual words in the text and the vector mathematics behind the search results in additional application scenarios such as the comprehensive search in foreign-language texts without their translation.

  • Artificial Intelligence
  • Intranet
  • Search
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