GENERATIVE AI / APPLICATION ENGINEERING

RAG, LLM & Intelligent Knowledge Systems

Making enterprise information usable through natural-language interfaces and connected AI workflows.

Retrieval-augmented generationMulti-LLM orchestrationEnterprise knowledge retrievalLLM integrationsAgentic workflows

Illustration for RAG, LLM & Intelligent Knowledge Systems

01 / OVERVIEW

The challenge.

Multi-LLM knowledge and question-answering applications, combining retrieval from structured and unstructured sources with practical interfaces and tool-driven workflows. Includes a WhatsApp-integrated hybrid LLM system from the résumé.

THE BIGGER PICTURE

Why this matters.

Organizations accumulate structured records, documents and operational knowledge that are hard to access through conventional search. Users often want direct answers in natural language rather than knowing which source or interface contains the information.

I have built hybrid LLM applications that connect different sources of information to conversational experiences, including a WhatsApp-integrated question-answering system described in my résumé. The focus is on useful, grounded applications rather than isolated model demonstrations.

MY CONTRIBUTION

From idea to working system.

Used retrieval-augmented generation, multi-LLM integration, structured and unstructured retrieval, and application interfaces. My experience also spans practical agentic workflows that connect language models with tools and business processes.

The value lies in making institutional knowledge discoverable, reducing the distance between a user question and relevant source material, and making intelligent assistance fit an existing workflow.

WHERE IT CREATES VALUE

Practical applications.

Natural-language access to enterprise knowledge

Integration of multiple information sources

Practical conversational interfaces

Extensible foundations for AI-enabled workflows

02 / WHAT I WORKED ON

Engineering highlights.

Hybrid retrieval across structured and unstructured information

User-friendly conversational access to knowledge systems

Integration of AI capabilities into applications and workflows

03 / TECHNOLOGIES & APPROACHES

Technical capabilities.

Retrieval-augmented generationMulti-LLM orchestrationEnterprise knowledge retrievalLLM integrationsAgentic workflowsApplication architecture

04 / PRACTICAL VALUE

What it enables.

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Faster access to relevant information

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Reduced friction for knowledge discovery

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Scalable AI-enabled workflows

Descriptions are high-level capability summaries. Client-specific designs, sensitive data, source code and proprietary implementation details are intentionally omitted.