Problem

Unable to generate realtime actionable intelligence

In many organizations globally, subject matter experts and users of all kinds are not able to view real-time actionable intelligence from their core business data. Instead, they spend time on arduous manual processes to generate static reports.

Improved by these Interventions

Integrate a Large Language Model (LLM) AI with a Knowledge Graph

Connect a Large Language Model AI service with a knowledge graph so that the information source is scoped and accurate. This provides a reliable information repository for using the LLM in a specific business area.

Technologies used

Machine Learning (ML)

Large Language Model (LLM) AI

Retrieval-Augmented Generation (RAG) with LLMs

Knowledge Graphs

Integrate ChatGPT with a Knowledge Graph

Integrate the popular LLM AI "ChatGPT" with a Knowledge Graph, so that an organization can use its own scoped and structured knowledge to provide the reference information for the AI.

Technologies used

Machine Learning (ML)

Large Language Model (LLM) AI

KGaaS - Knowledge Graph as a Service

ChatGPT - the LLM AI Product by OpenAI

Knowledge Graphs

Prevented by these Capabilities

Ability to view realtime actionable intelligence

Data Language regularly delivers the capability for staff, partners, and all business users to use live, real-time intelligence data.

Spatial data visualization and query capability

Graph data can be spatially aware, queried geospatially, and visualized on maps

AI services that enrich unstructured media with Knowledge Graph data

A business has services in place that automatically attach structured metadata conforming to a knowledge graph model to unstructured media. This might be archive media, live intelligence streaming from the web, confidential data, and more.

Leads to these Problems

SME resources wasted on low-value manual tasks