Hi everyone,

I'm a Data Analyst aiming to transition into AI Engineer roles focusing on LLM-based applications. I'm building a Graph-based RAG Medical Research Assistant using:
- NEO4j for graph database
- Ollama 3.1 for language model
- BioBERT for domain-specific embeddings

My goal is to showcase my skills in AI, graph databases, and NLP. Am I on the right track? Any suggestions to improve my project?

Looking forward to feedback!

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Right track

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Yup..
Nice plan..

Make sure to include mlops and ci/cd so that it mirrors a real production setup.

Demo projects are just a start but making sure they follow the production standards is the key.

Try to add observability (logging, tracing, monitoring, etc.) even for a small duration to just show that they could be added and to demonstrate your skills.

Also. If possible try to add some agentic ai application as well. They are a boom and will help you gather more traction.

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Got it!
Currently building relationship patterns between entities, analyzing condition patterns for better output. My system's doing:
- Organizes literature
- Answers questions
- Extracts biological entities

Adding MLOps, CI/CD, observability per your suggestion. Exploring agentic AI too.

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