How It Works

From Raw Interviews to
Grounded Theory in Four Steps

AI accelerates pattern recognition. You make every decision. Complete transparency from upload to insight.

play_circleWatch 2-Minute Overview

upload_file

UPLOAD

Bring your transcripts

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SEGMENT

Smart chunking

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CODE

AI-suggested codes you approve

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DISCOVER

Categories emerge from your data

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Drop files here

PDF, DOCX, TXT supported

.pdf

.docx

.txt

Step 1

Upload Your Transcripts

Drag and drop interview transcripts, field notes, or focus group data. Theoros handles the rest.

Supported Formats

PDF documents
Word (.docx)
Plain text (.txt)
Markdown (.md)

check_circleBatch upload multiple files
check_circleAutomatic text extraction
check_circlePreserved formatting

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Segment 1

Segment 2

Processing

Segment 3

Step 2

Smart Text Segmentation

Text is automatically divided into meaningful units — sized perfectly for analysis.

AI identifies natural breakpoints based on:

Semantic completeness
Speaker changes
Topic transitions
Natural paragraphs

check_circleNo manual chunking required
check_circleSegments ready for coding immediately
check_circleAdjust boundaries if needed

starThe Core of Theoros

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✓

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Step 3

AI-Suggested Codes You Approve

AI analyzes your segments and suggests codes based on patterns in your data — not imposed frameworks.

You're Always in Control — for each suggestion, you can:

Approve — Add to your codebook
Reject — Dismiss suggestion
Modify — Refine the code
Create — Add your own code

Suggested Code

psychologyAI Reasoning

Confidence

87%

Semantic92%

Pattern85%

Context84%

AI Reasoning Transparency

"Why did the AI suggest this code?"

Every suggestion includes full reasoning, confidence breakdown, and considered alternatives.

Every suggestion includes:

Full reasoning explanation
Confidence score breakdown
Similar segments considered
Alternative codes rejected

check_circleNo black boxes. Complete transparency.

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Step 4

Discover Emergent Categories

Categories emerge from your approved codes. See themes materialize from your data.

AI groups related codes and suggests categories:

Hierarchical structure
Visual relationship mapping
Drag to reorganize
Merge similar codes

check_circlePublication-ready category structure
check_circleComplete audit trail exported
check_circleEvery insight traced to source data

Throughout the Process

Every Decision Documented

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What AI Suggested

Every code proposal logged

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What You Decided

Approved, rejected, modified

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Why You Decided

Your notes and reasoning

The Foundation

Built on 50+ Years of Grounded Theory

Theoros doesn't replace your methodology — it accelerates it.

Our approach is built on the foundational work of Glaser & Strauss (1967), incorporating:

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Emergent Categories

Patterns arise from data, not imposed frames

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Constant Comparison

Continuous iteration between data and codes

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Theoretical Sensitivity

AI assists, human meaning-making guides

Learn More About Our Methodologyarrow_forward

Rigor Without the Grind

Traditional Manual

Theoros

Document Review

2-3 days

2-3 hours

Initial Coding

2-4 weeks

2-4 days

Axial Coding

1-2 weeks

1-2 days

Documentation

1 week

Automatic

TOTAL

6-10 weeks