Context-aware financial sentiment analysis.
Built on an open inversion catalog.
Standard NLP models get financial headlines wrong. “OPEC cuts” is not bearish for oil — it is bullish. swik applies Aspect-Based Sentiment Analysis (ABSA) with an asset-specific inversion catalog to return signals that reflect how markets actually react. Open data. Free API.
Why swik?
The Inversion Catalog
267+ known phrase inversions across 35+ assets. Context-dependent polarity corrections for commodities, FX, indices, and crypto. CC BY 4.0. Browse inversions →
Asset-Specific Sentiment APIs
Each security has its own price driver catalog. Direction, magnitude, and relevance calibrated per asset. Built for quantitative research and applications in trading.
Fine-tuning on Real Labels
Community labels feed LoRA fine-tuning per asset. Every contribution improves cross-asset spillover analysis and domain-specific model accuracy. Contribute →
Community-driven Accuracy
Every label sharpens the model. Top contributors earn API credits and appear on the public leaderboard.
See full leaderboard →