AI Interactive Tools
RAG Architecture Design Wizard
Generate a tailored 11-layer RAG architecture blueprint in 10 questions; vendor picks, KVKK + EU AI Act risk map, cost range, 3-phase rollout and PDF report.
- RAG Architecture
- RAG architecture is the discipline of co-designing ingestion, chunking, embedding, vector retrieval, reranking, LLM, guardrails, evaluation and observability so an enterprise language model produces accurate, auditable answers.
- Also known as: RAG architecture, retrieval pipeline, enterprise search architecture
How the wizard decides
Your answers feed a rule-based decision engine calibrated against the Q1-Q2 2026 vendor landscape. No LLM call is made: all recommendations are deterministic, run in your browser, and your data never leaves.
01
Hard constraints filter first
Deployment (on-prem / Turkey-only) and data sensitivity (KVKK special-category) apply first; incompatible vendors are eliminated.
02
Then scale and language
Document volume, concurrency and Turkish weight refine vector DB, embedding and reranker choices.
03
Use case picks the archetype
Legal/finance → citation-grade; customer support → low p95 latency; KVKK + on-prem → Turkey-local — six archetypes route the architecture.
04
Cost + rollout derived
Volume × scale × deployment multipliers give a monthly $ range; MVP (4-6 wk), V2 (6-8 wk), V3 (8-10 wk) deliverables flow from the scenario.
Frequently asked questions
Frequently Asked Questions
- CTOs, principal architects, AI leads, data teams and consultants designing a new or existing enterprise RAG (Retrieval-Augmented Generation) system. From SMEs to banks, public sector to SaaS — anyone who needs a defensible reference answer to 'what architecture should I pick?'.
Related tools and pages
Deepen the architecture decision across cost, compliance and training.
References
- Anthropic — Contextual Retrieval, Anthropic
- BAAI BGE-M3: Multi-Lingual, Multi-Functional, Multi-Granularity Embeddings, BAAI
- Qdrant Documentation — Self-Hosted Deployments, Qdrant
- Pinecone Serverless Architecture, Pinecone
- Microsoft Presidio — PII Detection & Anonymization, Microsoft
- EU AI Act — Regulation (EU) 2024/1689, European Union
- KVKK — 6698 sayılı Kişisel Verilerin Korunması Kanunu, T.C. Kişisel Verileri Koruma Kurumu
- Ragas — Evaluation Framework for RAG, Exploding Gradients
- Langfuse — Open-Source LLM Observability, Langfuse
- Mukayese Turkish NLP Benchmark, Mukayese