Deterministic answers from documented portfolio evidence
Evidence report3 sources · grounded response
Show me evidence of RAG
Here’s the evidence.
AutoCare Agent: Hybrid BM25 + all-MiniLM-L6-v2 dense retrieval evaluated across 100 diagnostic queries. 90% Recall@5 · local research. 100 diagnostic queries; 20 service manuals; approximately 4,500 document chunks. OpenSearch BM25 + all-MiniLM-L6-v2 dense embeddings through Sentence-Transformers. Decision-support POC, not a substitute for a certified technician. Recall describes the 100-query retrieval evaluation, not field diagnostic accuracy. Separate lexical/dense scores and scenario pass rates are not supplied. GenAI Research Assistant: 7,641 chunks and 76 queries; recall, throughput, build time and reported memory overhead. 7,641 Document chunks · local research. arXiv document corpus: 7,641 chunks, 76 queries. Unified VectorStore interface comparing FAISS/HNSW, Annoy and exact/Flat indexes; Sentence-Transformers embeddings. Local research application and retrieval benchmark, not a production service benchmark. QPS and index build time are not application request latency. Benchmark hardware, query distribution, recall cutoff and full per-backend outputs are not supplied. Intelligent Patient Admission Triage Assistant: Retrieval integrates with deterministic scoring and ML prediction in an in-progress local-first workflow. PostgreSQL + pgvector with BGE embeddings through Sentence-Transformers; local Ollama explanations. In-progress research/portfolio system; synthetic Synthea / FHIR-compatible records, no hospital production deployment or clinical-validation result. RAGAS/Langfuse evaluation and Prometheus/Grafana/Loki observability are designed/planned. No completed benchmark values are supplied.
Documented result90% Recall@5100-query retrieval evaluation (local research; completed): Recall@5 for hybrid retrieval. 100 diagnostic queries; 20 service manuals; approximately 4,500 document chunks. Recall@5: 90%. Hybrid retrieval over 100 diagnostic queries; profile-supported, evaluation artifacts pending. Indexed document chunks: ~4,500. Approximate corpus size: 20 service manuals. Service manuals: 20. Indexed automotive service manuals. Decision-support POC, not a substitute for a certified technician. Recall describes the 100-query retrieval evaluation, not field diagnostic accuracy. Separate lexical/dense scores and scenario pass rates are not supplied.
7,641 chunks and 76 queries; recall, throughput, build time and reported memory overhead.
Documented result7,641 chunks · 76 queriesANN / exact retrieval benchmark (local research; completed): Unified VectorStore comparisons across ANN and exact/Flat approaches; RAGAS end-to-end quality evaluation is documented without supplied numerical scores. arXiv document corpus: 7,641 chunks, 76 queries. Document chunks: 7,641. Benchmark corpus size. Benchmark queries: 76. Number of retrieval benchmark queries. HNSW recall: ≥0.998. Local HNSW retrieval benchmark; recall cutoff and aggregation not supplied. HNSW retrieval throughput: ~1,439 QPS. Local retrieval queries per second, not application request latency or production throughput. FAISS-Flat index build time: 0.002 s. Local index construction time; not request latency. FAISS-Flat reported memory overhead: 0.09 MB. Reported local benchmark memory overhead; measurement definition not supplied. Local research application and retrieval benchmark, not a production service benchmark. QPS and index build time are not application request latency. Benchmark hardware, query distribution, recall cutoff and full per-backend outputs are not supplied.
Retrieval integrates with deterministic scoring and ML prediction in an in-progress local-first workflow.
Documented resultEvidence-grounded explanationIn-progress research/portfolio system; synthetic Synthea / FHIR-compatible records, no hospital production deployment or clinical-validation result. RAGAS/Langfuse evaluation and Prometheus/Grafana/Loki observability are designed/planned. No completed benchmark values are supplied.