17.11.2020 | News How to optimize processes with AI and intelligent search
Enterprise search is actually a tool for extracting required information quickly and in a targeted manner from huge data stocks in companies and public authorities. The data sources can be structured or unstructured and the data can come from connected internal or external sources. To perform this task optimally, enterprise search is increasingly being enhanced with artificial intelligence. This includes machine learning or rule-based, linguistic and semantic processes.
This AI technology stack also considerably expands the field of application of enterprise search. With the AI-based analysis capabilities of the software, companies and public authorities can now optimize entire processes - and thus significantly accelerate the ROI for enterprise search once again. IntraFind explains five examples:
1. Processing applications. Through automatic text classification and NLP (Natural Language Processing), intelligent search software can automate the pre-qualification of forms and applications in government agencies. Applications submitted to application portals no longer need to be checked by humans for coherence and completeness. This work can be done by AI instead. Applicants are then notified during data entry that documents need to be corrected or supplemented, which speeds up the application process.
2. Sorting of documents. With machine learning techniques, an enterprise-wide search solution is able to identify categories into which data can be sorted. This can be used, for example, to identify document topics and sort the documents accordingly. This enables companies and public authorities to automatically analyze incoming e-mails and route them for response based on their content. In addition, it is even possible to send automatic replies containing further information.
3. Answering support requests. Service and support staff can use a central search function to find information quickly and easily across all data sources - be it service manuals stored on the intranet or spare parts catalogs available in special service information systems. As a result, they no longer have to access each system individually and deal with different operation methods. Using AI-based content analytics functions, they can go beyond a pure full-text search to find relationships between facts. This saves working time and customers get solutions to their problems faster.
4. Evaluating contracts. Based on modern machine learning methods, clauses and important data points in contracts or tender documents can be recognized and extracted for targeted review, risk analysis, commenting and processing. Specialist lawyers, for example, save a lot of time and enormous resources with this intelligent reading aid, as they no longer have to read contracts individually and manually mark their relevant points. They can devote more time to their core tasks and minimize the risk of overlooking crucial points. This pays off especially when large numbers of contracts need to be checked in the event of changes in legislation or company takeovers.
5. Picking applicants. With AI-based enterprise search, companies and recruiters can implement an intelligent applicant search in their HR systems. The software automatically identifies knowledge and skills in resumes and matches them with job profiles of open positions. In addition, HR employees are given the opportunity to search for required qualifications via free text and filter mechanisms and thus quickly find suitable applicants. This speeds up the recruitment process considerably.
"AI technologies - often in combination with intelligent searches - can significantly reduce the workload of people. Automation and augmentation allow employees to concentrate on tasks that require real human intelligence", says Franz Kögl, CEO of IntraFind Software AG. "But the human being is not only relieved. Many routine tasks can also be performed by software much faster and much less error-prone than by the human being himself".
