Smabbler :: Boost text preprocessing with Smabbler’s Graph Language Model.

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Semantic retrieval for Graph RAG

- to reduce hallucinations via extended context.

With knowledge graphs as an automated output,

Galaxia addresses the biggest graph RAG challenge
– efficient knowledge graph construction.

- Efficient information extraction from natural text
- Easy and quick retrieval of relevant text
- Using meaning and context for accurate results

Text labeling for controlled LLM fine-tuning

- to increase model accuracy.

Graph-powered automated labeling boosts fine-tuning by 10x.

High-quality data enables 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

- to detect unwanted or toxic content with LLM-independent output control.

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