The Insight Engine for Qualitative Text Data in Market Research & CX
deepsight transforms open-ended responses into reliable insights – fast, traceable, and GDPR-compliant. For teams whose results need to be visible and defensible internally.
Two ways to start: explore on your own or validate methodically with guidance – using your own data.
Live Analysis
From Comment to Insight
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Watch the automatic analysis...
Single Analysis
Trusted by leading companies
Open-ended feedback is the blind spot in your organization
You have thousands of open responses – but analysis is slow, expensive, and often methodologically questionable. That's where you lose speed – and trust in the results.
Manual coding consumes time & budget
With 5,000+ open responses, analysis takes weeks – time and resources you don't have.
Quality varies by coder/agency
Different coders, different results. Hard to compare and defend.
Insights arrive too late for decisions
By the time analysis is done, results are often no longer relevant for current decisions.
AI often seems opaque or unreliable
Many AI tools deliver results without traceability – problematic for research and stakeholders.
Reporting takes almost as long as the analysis
Results need to be prepared, visualized, and documented – an enormous additional effort.
There's a better way ↓
Best-in-class for a critical problem – not "just another platform"
deepsight is not a generic AI tool. It's a vertical solution for analyzing qualitative text data in research workflows – focused on speed, quality/traceability, and governance/compliance.
The AI for qualitative insights – not for everything.
What deepsight really is
Insight Engine
Topic & sentiment analysis, topic discovery, multilingual – powered by LLMs
Workflow Platform
Upload → Analyze → Export → Team Sharing – all in one interface
Execution Support
Transform results into actions/reports, standardized pipelines
Collaboration
Roles, team access, reproducible steps for the entire organization
Outputs that hold up in research reports
Results that are methodologically sound and presentation-ready.
Topics & Subtopics
Clusters, long tail, hierarchical structures
Drivers & Root Causes
Why is this happening? Root cause analysis
Segment Comparisons
Target groups, regions, waves compared
Quotes & Evidence
Evidence per topic, directly from the data
Export/Reporting
Codebook, tables, report-ready building blocks
Two ways to start
Depending on risk & maturity level
Exploration
Test independently, limited scope. Goal: Experience the aha moment and get to know deepsight.
Try itValidation
Guided process with your data: verify methodological, organizational, and economic viability.
Validate use caseTraceability & Compliance
See your open responses as structure – not as a wall of text
Start directly with your own data or validate your use case with guidance – including stakeholder assurance.