AI text analysis that holds up before ethics committees.
Citizen consultations with 50,000 free texts, longitudinal studies in 12 languages, consultations under time pressure – deepsight delivers the infrastructure social research needs: methodologically sound, reproducible, and GDPR-compliant.
Large corpora, strict methodology – and tight budgets.
Social research demands traceable results. At the same time, data volumes are growing – along with expectations for speed and transparency.
10,000+ free texts, too little capacity.
Citizen surveys and consultations generate text volumes that can no longer be handled manually. Research teams lose weeks – and the timeliness of their findings.
Reproducibility is demanded but rarely delivered.
Who coded what, when? Inter-rater reliability is standard methodology – but rarely documented systematically. Results stand on shaky foundations.
Multilingual data, one analysis.
Cross-border studies, EU consultations, multilingual panels. Separate pipelines per language increase effort and reduce comparability.
Features built for social research.
Not adapted, but designed – for qualitative content analysis, consultation processes, and academic studies.
Open & closed coding
Create your own code frames or let the AI discover topics. Both can be combined – everything versioned, everything traceable.
30+ languages, one code frame
Translate-then-analyze: All responses are translated and analyzed with one optimized model. Results comparable across language boundaries.
Automatic anonymization
PII detection and masking before analysis. k-anonymity for sensitive datasets – before any human sees the texts.
Reproducible & versioned
Document categories and check assignments against original responses to make the analysis traceable for other researchers.
Multiple coders, one system
Roles, assignment, conflict resolution. Senior reviews, junior codes – all with audit trail in the same system.
Complete audit trail
Who marked what, when? Which model suggested it? Full trace per data point – for ethics committees and peer review.
Where deepsight is used in social research.
From municipal citizen participation to EU consultations to academic longitudinal studies.
Citizen participation & consultation
Neighborhood surveys, urban planning, dialogue processes. 10,000+ free-text inputs systematically coded and clustered – in days instead of months.
Academic studies
Qualitative content analysis following Mayring or Grounded Theory – supported by AI, documented through audit trail. For dissertations, funded projects, and third-party research.
Policy evaluation & monitoring
Evaluate measures, measure impact, create reports. Structured analysis of interviews, position papers, and consultation processes.
Multilingual panels & EU studies
12+ languages, one code frame, comparable results. For cross-country studies, Eurobarometer analyses, and international research consortia.
Three paths – depending on what you need.
Not every research project fits into a SaaS tool. That's why we offer three entry points – from self-service to your own infrastructure.
Scientific standards, technically implemented.
GDPR & ethics
Germany hosting (Hetzner), DPA, no third-country transfers. Compatible with ethics committee and data protection officer requirements.
Anonymization
Automatic PII detection and masking – before analysis starts. k-anonymity for particularly sensitive datasets.
Audit trail
Every coding, every review, every model decision is traceable and exportable. For method sections and peer review.
Methodological review
Compare coding with an expert-reviewed sample and document differences.
Ready for methodologically sound text analysis?
Discuss your use case directly with our research team – whether cloud, on-prem, or hybrid.