This diagram represents how you can take scattered information and sources and convert them into AI embedded outputs called ai_workups using the knowledge_engine

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Key Features

Each knowledge_engine is grounded on the sources provided. While Large Language models like chatGPT relies on training data that is provided to it during the pre-training process, Decisional uses a combination of AI models to summarise and understand the sources you provide to add to the an AI model’s capability.

This grounding results in hallucination reduction, increased accuracy and trustworthiness

This allows knowledge_engines to gain some key capabilities:

  • Near Infinite Context: The knowledge_engine can hold as many sources as you require (we can hold tens of thosands of sources within a knowledge engine) and perform up to the same level of accuracy with minimal degredation in being able to fetch the right context
  • Transparent Citations: Each answer generated by the knowledge_engine can be linked back to one of the original sources you have provided through citations
  • Superior Accuracy: Decisional is able to tailor the models to perform better and be more accurate by making customisations for fine tuning AI models to perform better on Financial Services use cases

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Infinite Context

Since Decisional is pre-processing and analysing when you upload your sources, it has already learned from the knowledge you have provided. Additionally, Decisional uses vision models to understand logos, charts and images so that when you run AI workloads we can find the relevant context and use it appropriately.

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Transparent Citations

Every finding or information presented on Decisional is tied back to the original source through citations as illustrated below. This allows you to have an audit trail that substantiates facts and metrics.

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Superior Accuracy

Decisional measures accuracy on a popular benchmark called financebench and delivers industry leading accuracy.

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AI Workups

The knowledge_engine uses sources that you provide to generate AI embedded documents called ai_workups

An ai_workup is a type of document generated on the Decisional app that has an AI Agent embedded into it trained on the sources you provide that helps you write, find insights, generate tables, etc

Decisional allows you to produce two types of AI Workups

A magic_table is an AI powered spreadsheet which can generate cells based on all the sources you have provided to the knowledge engine. This is suited for more numerical workflows like compiling a table or quickly finding some information to screen a data room or a set of documents.

A memo is a long form document that can be used to write narrative driven research notes, thesis documents or reports typically suited for more qualitative work.

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The Knowledge Engine Interface

When you view a knowledge_engine there are three parts of the interface that you can see:

  • Source Explorer
  • Workspace
  • Decisional Assistant

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Source Explorer

The source explorer is visible on the left hand side of the knowledge_engine and titled as Sources. This lists all the the sources and the AI workups in the knowledge_engine including the ones you provide i.e documents, files or links. You can also add new sources by clicking on the ”+” button or clicking on the “Upload more” CTA.

The source explorer has a search bar that you can use to search throught all the sources and AI workups. Additionally clicking on one of the AI workups will change the editor experience in the Workspace.

You can collapse or uncollapse the source explorer by clicking on the collapse / uncollapse button or using the following command -

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Workspace

The workspace allows you to create and edit ai_workups like a memo or a magic_table . You can use the workspace to switch between different ai_workups through the workspace selector dropdown that shows you the current ai_workups that is being viewed along with an icon that indicates that type of workup it is.

Setup your first Knowledge Engine

Create your first knowledge engine and add a source to it