Features
Train Word2Vec, Doc2Vec, FastText models
Latent Semantic Analysis (LSA/LSI) training
Latent Dirichlet Allocation (LDA) training
Data streaming for arbitrarily large corpora
Similarity queries: most_similar, similarities
Pre-trained models via Gensim-data
Parallelized C routines for high performance
Cross-platform: Linux, Windows, macOS
Supports Python 3.8 to 3.11
Smart_open for remote storage access
Open-source (GNU LGPL license)
Commercial support available
Readable and extensible codebase
Semantic knowledge graph construction from enterprise data
Deep contextualisation of structured and unstructured data
Expert validation loops with versioned audit trails
LLM evaluation against accuracy and compliance criteria
Guardrails enforcing consistency from expert benchmarks
Full source traceability and explainable reasoning paths
Model-agnostic flexibility (no vendor lock-in)
Ingests documents, patents, regulations, research, and ERP data
330M+ documents securely ingested across 200K+ evaluated answers
Quantified confidence scores at every layer
Integrates with AWS for regulated deployment
Axion™ product: from data chaos to AI-ready intelligence
Neuralith™ product: enterprise knowledge into an AI engine
RSpace™ product: precision intelligence for complex R&D
Strategic partnership with AWS
