QuettaTopic
- Identifies and visualizes hidden trends across large document collections in real time.
- Delivers topic summaries and topic correlation insights to support faster decision‑making.
QuettaSentimentAnalysis
- Classifies unstructured text into sentiment labels (positive, negative, neutral) using AI
- Uses highly specialized sentiment models across industries and roles to deliver more accurate sentiment analysis.
QuettaSubjectClassify
- Automatically analyzes document subjects and assigns them to categories such as political, economic, or environmental.
- Provides industry‑specific classification schemes for precise and efficient document analytics.
QuettaNER
- Automatically extracts named entities like people, locations, and organizations from text.
- Supports trend analytics, market research, and sensitive information profiling for security applications.
QuettaSummary
- Generates concise summaries that capture the core content of a document.
- Offers configurable summarization engines and lengths for customized summary outputs.
QuettaKeywordExtraction
- Automatically extracts key terms and provides keyword ranking insights based on textual context.
- Enhances data analytics and search optimization workflows across use cases.
QuettaSpamDetection
- Automatically analyzes harmful spam and distinguishes promotional messages from genuine consumer content.
- Analyzes and filters malicious content to ensure high‑quality datasets for analytics.
QuettaBuzztype
- Infers and classifies unstructured text into Consumer, Paid, and Owned media categories.
- Enables more accurate measurement of real consumer reactions and data‑driven decisions.
QuettaPredict
- Learns statistical patterns from large-scale data to forecast future trends and time‑series changes.
- Detects anomalies in keyword, sentiment, and topic trends to predict future outcomes.