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JNACHI CERTIFIED RAG ARCHITECTView All 17 Certifications

Jnachi Certified Enterprise RAG Architect & Vector Specialist

Validates industry-standard engineering mastery in architecting production-grade Retrieval-Augmented Generation systems. Assesses vector database indexing (HNSW/IVFFlat), hierarchical and semantic chunking strategies, reciprocal rank fusion (RRF), Cross-Encoder rerankers, Knowledge Graph RAG, and continuous RAG evaluation using RAGAS/TruLens.

Format40 Proctored MCQs
Time Limit45 Minutes
Passing Score80% Standard
CredentialOfficial Diploma & Badge
Tier 020 Certification Exam80% Standard • Proctored

Jnachi Certified Enterprise RAG Architect & Vector Specialist

Validates deep expertise in architecting, optimizing, and evaluating production-grade Retrieval-Augmented Generation systems with hybrid search, semantic chunking, and knowledge graphs.

40
Questions
45m
Duration
4
Domains

Exam Competency Matrix & Domain Breakdown

Select any domain below to inspect tested skills, real-world scenarios, and preparation materials.

Domain Blueprint • 25% Exam Weight

Embedding Models, Vector Indexes & Chunking Strategies

Vector mathematics, embedding dimensionality, HNSW vs IVFFlat indexing, distance metrics, and advanced document chunking algorithms.

Assessed Competency Modules & Practical Scenarios:
Vector Indexing & Distance Metrics

HNSW graph navigation, IVFFlat inverted file lists, cosine similarity vs inner product vs Euclidean distance, and quantization techniques (PQ/SQ).

HNSW IndexingDistance MetricsProduct Quantization
Semantic & Hierarchical Chunking

Semantic boundary chunking, parent-child document relationships, sliding context windows, and table-aware document parsing.

Semantic ChunkingParent-Child IndexingTable Parsing

Portal Registration Required Before Exam

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Printed directly on your official diploma.

Used for attempt cooldowns & record retrieval.

Exam Objectives & Tested Competencies

1

Vector Indexing (HNSW, IVFFlat) & Semantic Chunking

Evaluated in scenario-based proctored questions.

2

Hybrid Search (Dense + BM25) & Reciprocal Rank Fusion (RRF)

Evaluated in scenario-based proctored questions.

3

Cross-Encoder Rerankers & Graph RAG Knowledge Graphs

Evaluated in scenario-based proctored questions.

4

RAG Triad & Automated Metric Evaluation (RAGAS / TruLens)

Evaluated in scenario-based proctored questions.

Exam Duration: 45 Minutes
Passing Criteria: 80% Score
Digital Credential: LinkedIn Verified Badge

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