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Decisional AI

Decisional-AI

Description

Decisional AI is an advanced tool particularly designed for financial analysts. Its main function is to generate AI memos by pulling information from a multitude of public and private data sources. Adapting to first principles-based qualitative research, this tool aids in crafting theses, accelerating due diligence, and accelerating portfolio management. One main issue it helps tackle is the constant context switching due to data silos and multiple sources of knowledge. Moreover, it helps reduce the time spent on clerical research work, thus assisting in deepening the thought process. Beyond the generation of memos, Decisional AI also has a unique feature that understands data and documents for auto-populating spreadsheet cells. It effectively helps to streamline workflows by eliminating manual tasks and easing metadata integration processes. With high reliability and security, this tool ensures data confidentiality with no model training required using your data. It supports multiple advanced Large Language Models (LLMs), and also features its proprietary models. It serves multiple types of queries and workflows. Decisional AI’s application range includes due diligence and portfolio management, competitive analysis, growth projections and Discounted Cash Flow (DCF) models and table extractions.

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Functionality
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Features
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Support
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Pros
24/7 support
82% more accuracy
Accelerates due diligence
Adapts to qualitative research
Allows table extractions
Application in due diligence
Applies for competitive analysis
Authenticates accuracy from sources
Auto-populates spreadsheet cells
Built for financial analysts
Caters to Private data sources
Eases metadata integration
Eliminates manual tasks
Embedded in multiple workflows
Enables DCF models
Enriches public companies’ data
Ensures data confidentiality
Features proprietary models
Handles large data volumes
High reliability and security
Minimizes clerical research work
Multiple query types
No model training required
Offers fact-based citations
Provides revenue data querying
Reduces context switching
Requires no complex integration
Saves user time
Setup 8 times faster
Streamlined back-office workflows
Streamlines workflows
Supports 5 users/account
Supports growth projections
Supports multiple language models
Supports multiple LLMs
Supports portfolio management
Supports queries and workflows
Uses public and private data
Cons
Data source restrictions
Limited to financial analysts
Limited types of queries
No mention of scalability
No model customization
Only supports Large Language Models
Potentially complicated to set up
Proprietary model restrictions
Unspecified data confidentiality methods

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