images/image-Photoroom.png 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 Each knowledge_engine is grounded in the sources you provide. Grounding is a process that ensures AI focuses specifically on your provided data rather than relying on its pre-existing training knowledge (which includes information from the internet and other sources). While large language models like ChatGPT depend on their original training data, Decisional combines multiple AI models to summarize and understand your specific sources. This approach enhances the AI model’s capabilities while significantly reducing hallucinations.
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 thousands 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
  • Deep Citations: Each answer generated by the knowledge_engine can be linked back to one of the original sources you have provided through citations . Decisional even highlights the relevant piece of information so that you can check facts for yourself.
  • 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.
Decisional performs up to 4X the accuracy of base foundation models. Detailed blog about this here.

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Near 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. images/upload_experience_2.gif

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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. Clipboard-20250607-023710-018.gif

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Superior Accuracy

Decisional measures accuracy on a popular benchmark called financebench and delivers industry leading accuracy. Finance bench is an open source benchmark for measuring performance of AI systems of financial queries like:
  • Given Company D’s recent expansion into Europe, what impact has this had on its revenue growth?
  • How has Company E managed its debt levels relative to competitors in the same sector?
  • What are the key factors contributing to Company F’s higher-than-average research and development expenses?

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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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Source Explorer - Viewer Along with listing the sources and ai_workups , the source explorer can also open up PDFs in the source explorer panel. This can be then used to navigate through a document or seach through it. If you need to view the whole document you can click on the “view” button or click on download from here to download the file to your computer. Source Viewer Gi

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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. Add A New Memo Block Gi images/workspace_2.gif

Setup your first Knowledge Engine

Create your first knowledge engine and add a source to it