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Netzwerk

How industrial companies benefit from enterprise search

Good decisions are based on readily available and relevant data.
The challenge here is that companies have growing volumes of data in a multitude of data silos and untapped potential in the use of data. AI-based enterprise search software enables fast and comprehensive access to information for all employees.
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How enterprise search boosts productivity, efficiency and innovation

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Link relevant data sources to a search: Search in e-mails, file systems, Confluence, NetApp and other applications

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Better customer service: provision of relevant information for customers and support staff

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Compliance and security: compliance with access rights and support in protecting sensitive information

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Better use of expert knowledge: easier access to specialist knowledge through the identification of experts

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Process optimization: Search as a central component for the automation and control of text-based processes

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Your advantages with iFinder Enterprise Search

  • Quickly find structured and unstructured information from different data sources
  • Rights-checked search for the highest security requirements
  • Scalability - future-proof solution even for growing databases
  • Automated data classification by topic
  • Personalization - find what employees are interested in
  • Flexible user interface - tailored to the needs of the company
  • Wide range of functions with a standard product
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Important application scenarios for Enterprise Search

The iFinder is not only a powerful tool for finding knowledge within the company - the software also demonstrates its strength in business-critical information processes.

  • Efficient information management
  • Optimized knowledge management
  • Avoid duplication of development work
  • Faster problem solving
  • Efficient customer service and support
  • Identify sensitive data for compliance

AI-based information management in industrial companies

In an information-based working world, companies should not only manage their enormous volume of data, but also exploit its potential and use it profitably. AI-based enterprise search software is the key to this.
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By combining search functions and powerful AI language models (Large Language Models, LLMs), iFinder enables the use of generative AI.

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The application goes far beyond a simple full-text search. It intelligently enriches data, identifies correlations and provides the user with suitable answers.

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Natural Language Processing (NLP) enables the search engine to better understand natural language search queries and deliver more relevant results.

Success stories of our customers

"The new search solution delivers the desired hits quickly, easily and reliably - the result: valuable time savings and satisfied users thanks to IntraFind."

Uwe Urra

Head of Product Documentation,
Technical Information & Central Archive
MTU Aero Engines AG
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IntrFind Case Study: MTU
"IntraFind stands for technologically high-quality products and reliability. The search specialists at IntraFind quickly understood our requirements with regard to the functionalities of the new search and were able to communicate their solution in an understandable way."

Thomas Müller

AUDI AG
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IntraFind Case Study: Audi AG
"With iFinder, we were impressed by the individual personalization options. In shipping, we search for specific shipping numbers several times a day and now save a lot of time with each search thanks to the search profile set up for our department. The resulting cost savings and customer focus speak for themselves."

Stefan Schäfer

Head of Dispatch Planning, WAREMA Renkhoff SE
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"With iFinder, we have succeeded in finding typically required documents up to 11 times faster, thereby significantly increasing customer satisfaction."

Director Technical Support

of a market-leading German company
in the field of mechanical engineering
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IntraFind Case Study: Bizerba

Discover the power of an enterprise search

Do you have a specific application or would you like more information? We will be happy to advise you.
 

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