Contextual Knowledge Mining

Contextual Knowledge Mining

The next wave of AI led transformation:

Over last 8 months, enterprises have seen unprecedented scale of digital transformation. This has resulted in exponential growth of organisational data within individual systems, conversation, documents, emails, online meeting, videos, chats etc. There are billions of internal and external events that are generated daily which could impact your decision making, which can’t be mined and reasoned through, using existing machine learning approach.

In a re-imagined world contextual knowledge mining will provide competitive edge, where ‘Collective intelligence’ are the new gold. While the first wave of AI involved many narrow applications, such as training a single model over one data source of a certain type for a single problem, contextual knowledge mining is the next wave of AI, generating a dynamic understanding of relationships and patterns in a corpus of information. It needs to be a key part of enterprise digital transformation initiatives that fundamentally change how organizations make sense of real-world information.

Organizations clearly need a means to discover and gain intelligence from all their data reliably and consistently. Contextual knowledge mining can transform the way businesses understand and leverage their content, exploiting the value in vast troves of previously untapped knowledge to create more insights and opportunities.

The next generation AI engine is a knowledge constellation dynamically connects events through various context and scenarios autonomously. Continuously learns and expands from events to create your own ‘Collective Intelligence’ which is ‘Always On’ intelligence, that enables auditable trustworthy decision making. It transforms your organisation to an intelligence enterprise.

Contextual knowledge mining can help solve three of the key challenges of handling unstructured information: time, scale, and insights. It drives better customer engagement, empowers employees, understand risks, predicts outcome while transforms products and services.

Here are some of the example use-case where I see a collective Intelligent Hub created by a neural engine preferably using knowledge graph married with deep learning to create a relational neural network. Not easy though to build and implement such engine !! Learning from real world data and creating dynamic relationship and insights is a recent progression in the AI research, if done well can provide the next generation knowledge mining.

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At Cognino, after years of research we have developed an Artificial Intelligence engine that addresses the volume , variety, velocity & veracity of data. The platform has the capability to continuously learn , comprehend the changing world events and providing a cognitive outcome, an “intelligent core” for the organization.

The platform benefits from next generation design, to deliver an ‘Always On” capability to address concerns around data and intelligence currency. Additionally, the solution also provides an in-depth view of all decisioning steps, bringing much needed transparency through explainable AI.

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