AIWave Discovery
Quick access to knowledge and corporate data is essential for productivity and effective decision-making processes. However, as companies accumulate large amounts of data and information across various systems, finding the right data at the right time becomes increasingly complex.
Enterprise Search solutions allow employees to efficiently retrieve the most relevant information, but traditional keyword-based methods often fail to provide accurate results.
AIWave Discovery provides a comprehensive set of tools for creating advanced search solutions in an integrated way.
It enables the construction of semantic indexes for document analysis and the integration of AI models (including new generative technologies) for Natural Language Processing, with the ability to integrate different sources thanks to a diversified range of connectors.
Capabilities
Index and Search
Performs indexing and content search based on semantic analysis engines enhanced by the latest generative composite AI technologies, allowing the extraction and indexing of text with respect to conceptual models.
Knowledge Access
Creates a single access point to various information sources, building a sort of “virtual knowledge base”.
Multi-source
This engine is able to collect data from different document sources without requiring the reorganization of documents, indexing them through a diversified range of connectors.
Work Memory
A system for storing searches allows direct access to already searched documents and quick updating of frequent search results. Successful searches are reported and can be quickly repeated.
Features and Benefits
Acquisition from heterogeneous formats and multilingual support.
Management of document visibility for public or private consultation.
Support for symbolic analysis through domain ontologies.
Retrieval of key information such as nominal entities and concepts to improve metadata and search accuracy.
Training of specific AI models for domains.
Natural language question answering with presentation of relevant documents and text portions.
Natural language search with semantic, conceptual, and structural understanding.
Use of content correlations to facilitate in-depth exploration through different navigation modes.
Vector search for similar documents.
Concept tree for documents or result sets.
Facet-based search filters.
Disambiguation and tolerance for typos.
Identification of entities and concepts.
Single access point for document search and consultation.
Logical Architecture
