VECTOR SEARCH AND RAG Solutions & Delivery Excellence
Alphaxine builds vector search and RAG pipelines that let your teams ask questions of maintenance manuals, contracts, SAP transaction history and internal knowledge bases, and get accurate, cited answers.
Document Ingestion
PDF, Word, SAP exports and ERP transaction data. Chunked, embedded and indexed into a vector store.
Vector Store
pgvector, Pinecone, OpenSearch or Weaviate, chosen for your scale and latency profile.
Retrieval Pipeline
Hybrid dense/sparse search with reranking, maximising precision of retrieved context.
Grounded Generation
LLM answers with source citations. No hallucinations about your own data.
Governance
Document-level access controls, audit logs and content filtering built into the pipeline.
Our Production Hybrid Vector Search & Retrieval Framework
Eliminating hallucinations by grounding generative AI responses in live ERP records, technical documentation, and proprietary enterprise knowledge.
Connect enterprise data silos (PDFs, SAP master data, SharePoint) with semantic boundary chunking and contextual metadata tagging.
Index embeddings in Amazon OpenSearch / pgvector, combining dense vector similarity with BM25 keyword matching and cross-encoder re-ranking.
Inject retrieved source passages with verifiable deep-link citations into LLM prompts, monitored by automated RAGAS factual accuracy scoring.
Speak with Our Enterprise RAG Architects
Build reliable, production-grade retrieval augmented generation systems grounded in your enterprise data.