// PRODUCTION DEPLOYMENTS & ARCHITECTURAL CASE STUDIES · SECTION 04

Flagship Systems & Production Impact

Technical architecture breakdowns of production systems, projects, and repositories this candidate has attached to their dossier.

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SYSTEM 01 // PROJECTRole: FEATURED PROJECT

Multimodal Financial Document Understanding System

Built a multimodal document-understanding pipeline using open-source vision-language models to extract text, tables, charts, signatures, and layout from multi-page financial documents, replacing traditional OCR-based extraction. Orchestrated the multi-stage pipeline using LangGraph, built a CrewAI-based validation agent using the ReAct pattern to verify extracted fields, and structured outputs into machine-readable JSON.

TechnologyMultimodal LLMs
StackLLaVA
PlatformQwen-VL
Metric 01—Pending
Metric 02—Pending
Metric 03—Pending
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SYSTEM 02 // PROJECTRole: FEATURED PROJECT

AI Hallucination Detection System

Built an LLM validation pipeline performing claim extraction, web evidence retrieval, and semantic similarity scoring to detect hallucinations. Integrated Google Gemini API and FAISS vector search for real-time evidence grounding. Designed an LLM observability layer providing trust scoring and reliability monitoring for AI-generated outputs, deployed via FastAPI with an interactive Streamlit dashboard.

TechnologyLLM Evaluation
StackRAG
PlatformFAISS
Outcomeachieving ~87% detection accuracySelf-reported
Metric 02—Pending
Metric 03—Pending
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SYSTEM 03 // PROJECTRole: FEATURED PROJECT

AskQL - Natural Language to SQL Query System

Built an AI-powered natural language-to-SQL system converting plain English queries into structured SQL commands using rule-based and NLP-driven pipelines. Applied classical NLP techniques for query understanding, with exploratory LLM-based enhancements and a modular architecture for future generative AI integration.

TechnologyNLP
StackSQL
PlatformLLM
Metric 01—Pending
Metric 02—Pending
Metric 03—Pending
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SYSTEM 04 // PROJECTRole: FEATURED PROJECT

Multimodal Financial Document Intelligence

Financial institutions process large volumes of dense, multi-page documents. Used open-source vision-language models (LLaVA, Qwen-VL) to jointly read text, tables, charts, signatures and layout directly from page images. Orchestrated extraction, validation, and structuring as a LangGraph pipeline with a CrewAI validation agent.

TechnologyLLaVA
StackQwen-VL
PlatformLangGraph
Metric 01—Pending
Metric 02—Pending
Metric 03—Pending
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SYSTEM 05 // PROJECTRole: FEATURED PROJECT

AI Hallucination Detector

Claim extraction breaks an LLM response into discrete assertions. FAISS vector search retrieves relevant evidence, and cosine similarity between embeddings produces a trust score. Deployed as a FastAPI service with a Streamlit dashboard.

TechnologyFAISS
StackGoogle Gemini API
PlatformSentence Transformers
OutcomeReached ~87% hallucination-detection accuracy on the evaluation set usedSelf-reported
Metric 02—Pending
Metric 03—Pending
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SYSTEM 06 // PROJECTRole: FEATURED PROJECT

Industrial RAG + Anomaly Intelligence

Built a RAG system over equipment logs and SOPs. Built a companion anomaly-detection pipeline across 1,400+ sensors and linked flagged anomalies to the retrieval system. Evaluated using RAGAS against a 100-observation golden dataset.

TechnologyLangChain
Stackpgvector
PlatformRAGAS
OutcomeReduced monthly troubleshooting job cards from 120+ to ~40 (~67% reduction) and cut root-cause analysis time by 55–60%Self-reported
Metric 02—Pending
Metric 03—Pending
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