AI Sentiment Analysis Pipeline for Social Media Monitoring

Ingest social media data from Twitter, Instagram, Facebook, and other sources into a centralized warehouse. 300+ connectors enable scaling data collection without custom code.

Fast, cost-effective LLM for batch sentiment analysis. Strong at nuanced emotion detection and brand context understanding with low hallucination.

Orchestrate daily/hourly sentiment analysis workflows. DAG-based scheduling handles data ingestion → processing → storage pipelines reliably at startup scale.

Store sentiment embeddings and historical analysis for trend detection and anomaly alerting. Enables semantic search across past brand mentions.

Monitor sentiment model drift, LLM output quality, and pipeline latency. Open-source observability prevents silent failures in production.

Transform raw sentiment scores into business metrics (brand health score, sentiment trends by region/product). SQL-based transformations scale with data volume.