Automatically discover what your customers are talking about
AI-Powered Topic Analysis
Intelligent Topic Discovery and Model Inference for deeper insights into your text data
With AI-powered topic discovery and analysis from deepsight cloud, you identify the most important themes in customer feedback, employee surveys, and open-ended responses – faster and more accurately than manual coding.
So funktioniert Topic Discovery
Der Preis ist zu hoch für das Gebotene
Schnelle Lieferung, sehr zufrieden mit DHL
Rabatt-Aktion war super, gerne wieder
Material fühlt sich hochwertig an
Versand hat leider etwas gedauert
Preis-Leistung stimmt hier absolut nicht
Die Qualität übertrifft meine Erwartungen
Paket kam beschädigt an
Analysis Methods
Analysis Methods
Choose the method for your use case
Topic Discovery (Standard)
Find topics automatically in your data with pure LLM analysis
- •Pure LLM analysis without embeddings
- •Highest quality for complex topics
- •Configurable: 3-15 topics
Topic Discovery XL (Hybrid) ⚡
10x faster, 25x cheaper through hybrid approach: Embeddings + Clustering + LLM
- ⚡Hybrid: Embeddings + K-Means + LLM
- ⚡10x faster for large datasets
- ⚡25x cheaper than pure LLM analysis
All three methods complement each other perfectly: Topic Discovery (Standard) for highest quality, Topic Discovery XL for large datasets, Model Inference for consistent classification with trained models.
Thousands of Texts, Which Topics?
Thousands of Texts, Which Topics?
Manual categorization of feedback is time-consuming and subjective. Important topics remain undiscovered. Standard tools only find keywords, not real topics.
Manual categorization is time-consuming and inconsistent
Important topics remain hidden in large datasets
Keyword search doesn't find semantic relationships
Subjective ratings lead to biased results
Die Lösung
Intelligent Topic Discovery
Our AI analyzes your texts in two phases:
Automatic Topic Detection
GPT-4o finds main topics in sample analysis (50-100 texts)
Multi-Label Classification
Each text receives scores for all topics (0.0-1.0)
Semantic Understanding
Related concepts are grouped, not just keywords
Model Inference
Free LLM analysis with custom prompts for specific questions
Themen verfeinern
Passen Sie entdeckte Themen an Ihre Anforderungen an – umbenennen, zusammenführen oder neue hinzufügen
Anwendungsfälle
Use Cases
Where Topic Analysis is used
Understand Customer Feedback
Which features are most requested?
- Automatically identify feature requests
- Detect most common problems
- Prioritize product improvements
Employee Feedback
What topics concern your employees?
- Capture sentiment in teams
- Identify important concerns
- Derive targeted actions
Enterprise Analytics
Analyze large datasets in a structured way
- Scalable analysis for large organizations
- Consistent categorization across teams
- Automate recurring processes
FAQ
Frequently Asked Questions
Configurable: 3-20 topics. Default: 8 topics (optimal for most use cases).
Yes! Multi-label classification: Each text receives scores for all topics.
Keywords find individual words. Topic Discovery understands semantic relationships and groups related concepts.
Yes! AI suggests names, you can manually rename them.
Flexible module: You define custom prompts like 'Extract main points' or 'Categorize as Bug/Feature/Praise'.
More Modules
Discover Related Modules
Combine modules for a complete analysis workflow