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AI-Powered Comment Analysis
Stop reading thousands of survey comments manually. Our NLP engine automatically clusters themes, scores sentiment, and surfaces the top topics requiring leadership attention.
Key Capabilities
Everything you need to make ai-powered comment analysis a competitive advantage for your organisation.
Sentiment Classification
Every comment is classified as Positive, Neutral, or Negative with a confidence score, giving instant polarity overview.
Topic Clustering
Machine learning groups comments into automatically-detected themes such as 'Work-Life Balance', 'Manager Effectiveness', 'Career Growth'.
Priority Matrix
Comments are plotted on a frequency × sentiment matrix, so you instantly see high-frequency negative themes that demand action.
Multilingual NLP
Our model processes comments in Arabic, English, French, and 20+ languages — no translation needed before analysis.
Keyword Extraction
Named-entity and keyphrase extraction surfaces specific terms, names, and processes that employees reference most.
Anomaly Detection
Flags statistical outliers — unusually negative comment clusters by department or demographic — for immediate manager review.
Time-Series Sentiment
Track how sentiment around a specific theme (e.g., 'compensation') evolves across survey waves.
Export & Redaction
Export themed comment tables with auto-redaction of personally identifiable information for safe shareability.
Frequently Asked Questions
Our model achieves 92%+ accuracy on HR-domain Arabic and English text, trained on a proprietary corpus of 2M+ employee survey comments.
Yes. The AI processes aggregated comment data and applies automatic PII redaction before any results are surfaced to administrators.
Yes. Enterprise clients can supply a custom glossary of company-specific terms and acronyms for domain adaptation.
Currently Arabic, English, French, German, Turkish, Urdu, and 20+ additional languages. New language support is added quarterly.
For surveys of up to 10,000 responses, full NLP analysis typically completes within 15 minutes of survey close.