Queria Architecture v3.5.0
Queria is not a simple document search engine. It is a cognitive intelligence platform designed to understand complex questions, reason on information and produce accurate answers with verifiable citations.
At the heart of everything is Cog-RAG (Cognitive Retrieval-Augmented Generation), a proprietary architecture that overcomes the limits of traditional RAG systems.
What makes Queria different
Conventional RAG systems follow a linear path: receive a question, search similar documents, generate an answer. It works for simple questions but fails when complexity rises.
Cog-RAG introduces a layer of cognitive reasoning between the question and the answer. The system analyzes intent, plans a search strategy, decomposes complex queries into sub-problems, verifies result quality and synthesizes information from multiple sources into a coherent and cited answer.
User question
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[Planner] ---- Intent analysis and routing
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Query decomposition (if needed)
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Multi-source search
- Company documents
- Knowledge Base
- Certified external sources
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[Reranker] ---- Semantic re-ranking
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Quality and grounding check
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[Writer] ---- Synthesis and deep reasoning
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Answer with citations [1][2][3]The four pillars
Intelligent retrieval
Search combines semantic similarity and lexical matching in a hybrid system that automatically adapts to question complexity. For simple queries, the system is fast and precise. For complex queries, it widens the search radius and lowers thresholds to ensure complete coverage.
Multi-agent reasoning
A set of specialized agents collaborates to answer questions. Each agent has a precise role: query analysis, search, result evaluation, anti-hallucination verification and final synthesis. The process is transparent and the user can follow each step of reasoning.
Privacy by design
The multi-tenant architecture guarantees full isolation between companies. AI models run on dedicated local infrastructure, without sending data to third-party cloud services. Every aspect of the system is designed for native GDPR compliance.
Multi-source integration
Beyond company documents, Queria integrates certified external sources in legal, food, chemical and pharmaceutical domains. Results are unified, re-ranked and presented with colored badges identifying the origin of each piece of information.
Why Cog-RAG for enterprise
Organizations that manage complex documentation have needs that traditional RAG systems do not meet:
Questions spanning multiple documents: a legal operator asks for the comparison between two regulations. Cog-RAG decomposes the question, searches in parallel and synthesizes a structured comparison.
Answers requiring reasoning: a quality manager asks if a product complies with a specific regulation. The system doesn't just find the document, it reasons about compliance.
Reliability and traceability: every claim in the answer is linked to the source document. No invented information, no hallucinations. If the system doesn't find sufficient evidence, it states this explicitly.
Data sovereignty: company data remains in the organization's infrastructure. No cloud AI vendor has access to documents.
Cog-RAG is designed for enterprise scenarios where precision, traceability and confidentiality are not optional but fundamental requirements.
Architecture sections
| Section | Content |
|---|---|
| Cog-RAG | Cognitive architecture, two-brain system, query orchestration |
| Agents | Multi-agent system, collaborative pipeline, anti-hallucination |
| Privacy | Multi-tenancy, GDPR by design, encryption, data sovereignty |
| Pipeline | Document processing, OCR, chunking, indexing, generation |