Purpose

Help workspace admins understand the different data sections within a deal and how each contributes to DiligenceGPT’s AI-powered analysis and reporting.

Overview

Each deal in DiligenceGPT contains structured data that powers analysis, scoring, and reporting. Data comes from multiple sources, including founder submissions, uploaded documents, and automated website scraping. All information entered or extracted across the deal feeds the platform’s AI models, providing insights for Deal Fit, startup scoring, and reporting.

Website Analysis

DiligenceGPT can automatically scrape the startup’s website to extract key information about the company. This includes descriptions, team info, product details, and other publicly available data. Website analysis helps populate deal fields quickly, saving time and improving the completeness of deal data.

LinkedIn Info

DiligenceGPT collects publicly available information from a company’s LinkedIn profile, including the company description, industries, size, location, and recent updates. This data is then used to enrich the deal profile, providing a more complete view of the company for review, analysis, and reporting.

Deal Info

Deal info combines auto-extracted data (from website, documents, or applications) with manual edits entered by your team. This ensures that all relevant information is accurate, up-to-date, and complete.

Data Statuses

Every data field has a status to indicate its completeness and verification level:

• Missing: Required data is not yet available
  

• Pending Review: The data entered may include AI-generated content, which is subject to review before it is finalized. To accept or modify the AI-generated suggestions, this can be done:
  

This process ensures that all AI outputs are accurate and aligned with the team’s standards before being saved.

• Approved: Data has been verified and is ready for analysis

Statuses help your team quickly identify gaps and prioritize data collection for each startup.

Deal Wall (Notes)

The Deal Wall allows team members to add notes about a startup. Notes can include observations, updates, or context that isn’t part of official documents. All notes contribute to AI analysis and help teams capture qualitative insights across deals.

Data Room (Documents)

The Data Room is where all uploaded documents—pitch decks, financials, or other files—are stored. Documents are used to feed AI models for scoring and reporting. Organizing documents in the Data Room ensures the AI has access to complete and accurate information.

Questionnaires

The questionnaire is configured at the workspace level through the workspace settings. Once set up, the same set of questions is automatically applied to every deal within that workspace. AI uses these questions to generate initial answers for each deal, ensuring consistency in data collection and providing a structured starting point for analysts to review, validate, and refine the information.

How All Data Feeds AI Analysis

Every piece of information entered in these sections—website, LinkedIn, deal info, notes, documents, and questionnaires—is used by DiligenceGPT’s AI models. The AI aggregates and analyzes this data to generate:

• Deal Fit scores

• Startup evaluation summaries

• Risk assessments and scores

• Dynamic reports for teams and decision-making

This ensures your analysis is data-driven, comprehensive, and consistent across all deals.

Understanding and maintaining complete deal data is critical. The more accurate and complete the inputs across all sections, the more powerful and reliable the AI-generated insights, scores, and reports will be. Learn more in Moving a Deal Through the Due Diligence Process.