Aiimi Insight Engine Disco
User GuidesAiimi
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    • Creating a Native Enrichment Step
      • Creating an Enrichment Step
        • Creating the Core Classes
        • Extending our Enrichment Step
        • Adding a Configuration Template
        • Adding the Enrichment Step
        • Creating an Enrichment Pipeline
      • Other Tasks
        • Entities, Metadata and Data
        • Accessing the Repository
      • Example Code
      • Troubleshooting
    • Creating a Python Enrichment Step
      • Creating an Enrichment Step
        • Running the Example from Command Line
        • Running the Example
      • Creating Your Own Step
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  • whitepapers and explainers
    • Methods for Text Summarization
      • Application
      • Technology Methods
      • Commercial Tools
      • Key Research Centres
      • Productionisation
      • Related Areas of Text Analytics
      • Conclusion
      • References
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On this page
  • Introduction
  • AIE has following key concepts:
  • Source Connectors
  • Enrichment
  • Repository
  • Gateway & API
  • User Interface
  1. Architecture

Overview and Key Concepts

Introduction

Aiimi Insight Engine is an information management platform that brings unstructured and structured information together. It offers users a fundamentally different way to consume information. Leveraging links between, recommendations, machine learning, user personas and other next generation capabilities.

AIE has following key concepts:

Source Connectors

Connecting to source systems that have documents or data that need indexing into Aiimi Insight Engine. They provide the initial load and then provide deltas (new, updates and deleted items). Source connectors follow the same pattern and are underpinned by a framework. This enables Aiimi, our customers and our partners to create new connections quickly. There are many connectors out of the box, but we are always updating this with new connectors.

Enrichment

Adding context to items Aiimi Insight Engine discovers using the enrichment pipeline. Most are labels that are applied to items. This helps Aiimi Insight Engine present more meaningful information to users. Enrichment may add classifications, geotags, named entities and other such things to items. Like source connectors, they are extensible and underpinned by a framework. This makes it easy for both Aiimi, our customers and partners to create enrichment steps. Enrichment steps are generally written in .NET or Python, but can be any language and interfaced using a generic REST enrichment step.

Repository

Repository is where Aiimi Insight Engine stores all the items it discovers and enriches. Along with the data and documents, configuration, permissions and other information is stored. The repository is based on Elasticsearch. This provides excellent scaling and performance for massive enterprise data sets.

Gateway & API

The gateway hosts a series of REST APIs used to access data and documents stored within the repository. The gateway is also responsible for authenticating users and authorising what they can see. (e.g. permissions trimming results). The APIs are used by our own apps, but can also be used by our customers and partners to create their own apps and integrations.

User Interface

The user interface is as a collection of apps to access the information within Aiimi Insight Engine. The apps are HTML5/CSS/JavaScript but, can be anything that can communicates with the Gateway using HTTPS and REST.

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