Overview
Delve’s AI features are designed to assist researchers in analyzing qualitative data faster and more efficiently. AI in Delve acts like a research assistant, helping you brainstorm ideas, generate codes and subcodes, summarize transcripts, and uncover patterns within your data. However, it is important to remember that AI tools do not replace your expertise - they assist, but you still need to critically evaluate results and understand your research context.
Note: All AI features require joining Delve’s AI beta program. You must accept the Beta Terms to access AI Chat, Transcript AI, and Apply Codes Using AI.
Delve provides three AI tools to assist with qualitative analysis: Transcript AI, AI Chat, and Apply Codes Using AI. Each tool has unique capabilities, inputs, and recommended uses. Understanding how they work and their limitations will help you make the most of Delve’s AI features.
Overview of Delve AI Features
Transcript AI: Analyzes a single transcript using your existing codebook to suggest high-level codes, themes, and relevant quotes.
AI Chat: Allows deep interaction with coded snippets across your project, helping you brainstorm subcodes, refine codes, summarize snippets, and clarify insights.
Apply Codes Using AI: Automatically applies your existing codes to transcripts based on code names and descriptions (deductive coding).
These tools can be used together in sequence for efficient qualitative analysis:
Start with Transcript AI for a high-level overview of one transcript.
Use AI Chat to refine codes, create subcodes, summarize snippets, and explore patterns across transcripts.
Apply Codes Using AI to systematically code transcripts using your refined codebook.
How Each Tool Works
Transcript AI
Purpose: Generate high-level codes, summarize transcripts, and suggest quotes.
Inputs:
Individual transcripts (you can only use the AI tool to analyze one transcript at a time)
Your existing codebook
Outputs:
Suggested codes/themes
Summarize transcript
Suggest quotes from transcript to support themes or codes
Citations linking to your transcript to verify quotations and sources
Limitations:
Only sees the selected transcript and your codebook.
Cannot see previously coded snippets.
Recommended Use:
Start your analysis with Transcript AI for a single transcript.
Use its output to guide deeper coding in AI Chat.
AI Chat
Purpose: Assist in deeper analysis and refinement of coded snippets.
Inputs:
Selected coded snippets or transcripts (you can filter by code, transcript, or both).
Outputs:
Ideas for subcodes, new codes, summaries, or code descriptions
Identifying potential snippet outliers
Suggestions you can evaluated for accuracy and relevance
Citations linking to your snippets to verify quotations and sources
Recommended Use:
The AI works with a subset of your data at a time, so filtering by code, transcript, or both will give you the most targeted insights. (It will let you know if it's only analyzing a portion of your data.)
Refine codes and subcodes after a first round of broad coding.
Summarize code collections and create code descriptions.
Explore nuanced patterns across multiple transcripts.
Works best iteratively with specific prompts
Use AI generated Code Descriptions to improve your Apply codes using AI.
Apply Codes Using AI
Purpose: Deductive application of your refined codebook to transcripts.
Inputs:
Individual transcript
Existing codebook (code names and descriptions)
Outputs:
Applies codebook to selected transcript (AI-applied snippets)
Memos explaining why each code was applied to the snippet
When to use:
After your codebook is complete or refined
To speed up coding across transcripts
Recommended Use:
Works best with a well-defined, specific codebook - clear, distinct code descriptions lead to the most accurate results
Performs optimally when codes have minimal overlap - refining definitions to reduce ambiguity helps the AI apply codes more precisely
Designed for a human-in-the-loop workflow - iterating with human review ensures the highest quality and reliability over time
Suggested Workflow
Transcript AI – Generate high-level codes and summaries for a transcript.
AI Chat – Refine codes, create subcodes, and summarize snippets.
Apply Codes Using AI – Systematically apply refined codes to transcripts.
Iterate – Use AI Chat and manual review to adjust codes as needed.
AI Feature Comparison Table
Feature | Inputs | Outputs | Ideal Use Case | Key Limits |
Transcript AI | Single transcript + codebook | Transcript summary, suggested initial codes, highlighted quotes | Early-stage coding, high-level overview | Limited context, does not see already coded snippets |
AI Chat | Filtered coded snippets | Subcodes, code summaries, new code ideas, customizable answer formats | Refining codes, summarizing snippet collections, brainstorming | The AI can only analyze a subset of snippets at a time, so filtering by code, transcript, or both is recommended for larger projects |
Apply Codes Using AI | Transcript + codebook | Automatically coded transcript, AI memos explaining decisions | Applying finalized codebook efficiently | Accuracy depends on codebook quality, human review suggested |