Insight Platform Overview

The challenge is to get information into the hands of knowledge workers. The data-driven enterprise does this (but only for data, not content) by relying on the cognitive effort of the knowledge worker. This imposes a cognitive burden, which refers to the extra thought and effort that we humans require to evaluate the available options and make optimal decisions. . This burden hinders corporate performance and opportunity. There are four capabilities needed to become information-driven. Sinequa provides these capabilities, thereby reducing the cognitive burden. Those capabilities are content, meaning, learning, and presentation.

Insight Platform Interface

Content

Sinequa is unmatched in its ability to provide a single search experience by unifying all content and all formats across all sources into a single platform. This is accomplished through our library of over 200 ready-to-go connectors and built-in converters that support over 350 document formats, so accessing content across multiple sprawling enterprise systems is a breeze. All connectors and converters are included in the platform, and Sinequa regularly adds to this library, typically developing another 10-20 connectors every year. This enables rapid deployment across all common enterprise information assets (including both structured and unstructured content) for the most comprehensive consideration across the enterprise digital landscape.

Content

Meaning

Sinequa provides multiple text mining capabilities that go well beyond simple keyword matching, including deep text analysis, Natural Language Processing (NLP), and extensible text mining agents.

The Sinequa platform is a fully semantic solution, incorporating the depth of over 25 years of linguistics research as well as the latest text analytics technology. Many layers of analysis are applied to extract meaning from unstructured text, and are then brought together to provide the most relevant and accurate results.

Meaning
Meaning

Learning

The Sinequa platform provides Machine Learning (ML) and Deep Learning (DL) algorithms that complement the platform’s deep integration with existing ML and DL frameworks to provide an “Enterprise Ready” solution that supports the creation, management and execution of ML/DL projects without the need for software development.

This integration enables the citizen data scientist to configure select ML/DL algorithms on top of industry computation frameworks and choose what data to feed into the projects from the Sinequa enriched indexes. The output of these algorithms are subsequently written back into the Sinequa indexes for analysis, exploration and search-based applications.

Presentation

The Sinequa platform offers a simple, intuitive, and familiar user interface framework that is flexible to accomodate the configuration of search-based business solutions and other types of information-driven applications built on top of the platform.

The configuration options of the Sinequa platform are accessible via a Web-based administrative interface that enables administrators to manage the main features of the solution. Via the Web administration interface, it is possible to simply adjust the settings according to contextual or business profiles, visibility of sources or relevance between sources, navigation boxes, activation of specific synonyms, graphs, advanced search, sponsored links, look and feel, etc.

The Sinequa solution also provides intuitive APIs that enable the platform to be seamlessly integrated into other environments without changing the existing experience of the end user. For example, REST calls can return results in XML or JSON.

Emergent Capabilities

Expert Networks

With the ability to surface exhaustive information on any given topic comes the ability to identify the network of experts on these topics. This is useful in building more productive, purpose-built teams, more quickly as well as in finding the right person for the job when specialty tasks arise. This approach can extend across many use cases such as personnel retirement – i.e. when the organization seeks to fill the role internally with existing talent rather than hire new staff – to processing legal matters more quickly and efficiently by identifying experienced attorneys in your firm to accelerating time to market for a new drug by streamlining the work of research and development teams to putting together the right teams quickly for an RFP response or to work on a customer project.

360° View

The ability to surface all relevant information associated with person, topic or thing allows organizations to build a comprehensive profile of that person or entity. Depending on the use case, this ability to surface holistic information and insights from across silos of content and data can mean anything ranging from increased revenue due to superior customer service to more market share due to deep competitive intelligence to tremendous cost savings/avoidance due to the ability to comply quickly and confidently to industry regulations.

Learn More

Becoming an Information-Driven Organization

Check out Scott Parker’s presentation during the KM World 2018 summit.

Sinequa’s Cognitive Search & Analytics Platform

Learn more on becoming Information-Driven with Cognitive Search and Machine Learning and how cognitive search platform will fit perfectly with your system.

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