One platform instead of scattered tools
Separate AI components carry a hidden cost: a vector store in one place, an API adapter in another, a script for evaluation somewhere else. The ESTAYA AI Platform brings these layers into one documentable system. At its centre sits a gateway built on LiteLLM. It standardises access to open-weight models such as Llama, Mistral, Qwen and Teuken, which we run ourselves with vLLM. You stay free of vendor lock-in and can swap models without rewriting your applications.
Answer quality comes from several methods rather than a single retrieval step. Citation-grounded RAG ties every statement to its source. PageIndex places long documents in structure, a knowledge graph connects entities, and an NLI check discards claims the context does not support. Our own algorithms sharpen selection: Reciprocal Rank Fusion merges multiple result lists, cross-encoder reranking orders by relevance, and context-adaptive weighting adjusts to the query at hand.
AI agents follow a Plan-Execute-Reflect pattern and connect to your systems through the Model Context Protocol. Governance and observability record every call, model and source so each result can be traced. With the eval_harness and RAGAS we put a number on retrieval quality and faithfulness.
- Model independence through a single gateway
- Verifiable answers via grounding and NLI checks
- Proprietary ranking algorithms beyond plain vector search
- Deployment on-premises, in your VPC, or as SaaS on our own servers in Germany
- In production in the ESTAYA AI Platform and a large-scale AI archive with millions of documents
GDPR, the EU AI Act, BSI IT-Grundschutz and ISO 27001/42001 form the framework we implement for you. Beyonetix itself is not certified. What we provide are traceable logs your own audit can use to evidence these requirements.