_{Agentic RAG · Knowledge Graph · Semantic Layer · MLOps}

A domain-adaptable assistant that answers with evidence or abstains.

A master orchestrator routes requests to five specialists using vector retrieval, reranking, structured metrics, and a knowledge graph. Deterministic gates block PII, prompt injection, unsafe actions, and unsupported questions before the model runs.

Retraining is automated, while model promotion stays human controlled.

500 tests 85.9% routing 100% escalation recall 430× lower cost

FastAPI LangGraph Qdrant Cohere Groq Neo4j dbt MLflow Langfuse

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_{NLP · Clustering · Statistical Validation}

Turns 83K social posts into evidence-backed personas.

Behavioral signals are clustered, then validated using Fisher or chi-square tests with false-discovery-rate correction. Each persona is supported by statistically significant patterns, not only visual clusters.

83K posts Validated personas 23K+ tests

DSPy GEPA HDBSCAN K-Means Fisher BH-FDR

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_{LLM Extraction · Classification · Cost-Aware Design}

Classifies whether a misrouted lead should be refunded.

Moving a key decision from the model into a deterministic rule improved precision from 0.43 to 0.89, without using a larger model.

.43 → .89 precision Same model Lower cost

LLM Extraction Embeddings XGBoost Rules Shadow Mode

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_{MLOps · Drift Detection · Continuous Training}

A five-stage lifecycle connecting production monitoring to retraining.

PSI drift triggers retraining, challenger evaluation, artifact tracking, and human-reviewed promotion.

5-stage loop PSI monitoring Zero manual scheduling

FastAPI MLflow Docker AWS CI/CD Model Registry

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_{Search · Reranking · Safe RAG}

Combines BM25 and semantic retrieval using reciprocal rank fusion and reranking.

The guarded RAG layer answers from retrieved evidence, blocks prompt injection, and limits SQL to SELECT-only queries.

+22% relevance Sub-second A/B tested

FAISS BM25 SBERT RRF Reranking LangChain

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_{Multi-Agent System · Analytics · Secure Execution}

Turns natural language into SQL, charts, statistics, and predictions.

A central orchestrator routes work to seven specialists with schema validation, sandboxed execution, and 40+ security checks.

91% routing 7 agents 195+ tests

FastAPI MCP Plotly Docker SQL Python

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_{Human-in-the-Loop · SQL Safety · Fallbacks}

An AI analyst that asks before it acts.

A three-stage approval flow protects sensitive operations. SQL is checked at the AST level, writes are blocked, and deterministic fallbacks keep core analytics available.

154+ tests 1M+ records Zero writes

FastAPI Gradio MCP SQLite AST Validation

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_{Safety rules and approval gates live in code, not prompts.}

_{Models are selected by quality, latency, cost, and failure analysis.}

_{Rules and smaller models handle simple requests first.}

_{Retraining is automated. Production promotion is controlled.}

LangChain LangGraph Qdrant FAISS BM25 SBERT Cohere Neo4j RRF Reranking

MCP DSPy GEPA Groq Multi-Agent Routing Human-in-the-Loop Guardrails

MLflow Langfuse RAGAS FastAPI Docker CI/CD Model Registry Drift Monitoring

PyTorch scikit-learn XGBoost Transformers Embeddings Clustering

Spark PySpark Databricks dbt DuckDB PostgreSQL AWS Azure

Python R A/B Testing Causal Inference Fisher Chi-square BH-FDR