Other applications
Fine - tuning
Graph-powered automated labeling boosts fine-tuning by 10x. High-quality data enables to F1 score improvement by 2.5x.
Source of labels independent from LLMs
Full control over labeling changes
Easy to expand topical knowledge
Guardrails for LLMs
Galaxia enables quick semantic and contextual validation of user queries and LLM output to support ethical and safe AI applications.
Result transparency
Full control over changes
Topics, sentiment, context and their co-occurrence monitoring
Feature extraction from text
Easy to expand topical knowledge
Quick ML model deployment
High ML model performance
Check out our ML example on Hugging Face: Multiclass-Disease-Diagnosis-Model.
Graph-based embeddings
Broader context for AI models
Semantics and similarities
Easy content navigation for chatbots
AI knowledge base
Knowledge for AI models
Context enrichment
Semantics, similarities and metadata
Structured data for BI / process automation
Applicable to multiple domains
Quantifiable and consistently formatted data
22 languages out-of-the box
Easy to extend to other languages
Topic detection
Applicable to topics, sentiment, context and their co-occurrence
22 languages out-of-the box
Easy to extend to other languages
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