Generative AI final year projects (14 to choose from)
Generative AI is the fastest-growing area in computer science, and a project built on large language models (LLMs) shows reviewers that you understand current technology. The 14 projects on this page include RAG-based document question answering, domain chatbots, resume and interview assistants, research-paper summarisers, multilingual customer support and task-automation agents.
Most projects combine an LLM with retrieval-augmented generation (RAG): documents are split into chunks, converted to embeddings, stored in a vector database and retrieved at query time so answers stay grounded in real content. You also get hands-on experience with prompt engineering, conversation memory and response evaluation.
Every listing comes with source code, a project report, a PPT and an installation guide, and each has a dedicated detail page covering the abstract, modules, workflow, technology stack and likely viva questions.
Generative AI Project List
Source Code + Report + PPT + Installation Guide — click any title for full details, or enquire on WhatsApp.
To buy a project, contact us on WhatsApp (+91 9688163291) or call 9688163291 / 8270827832. After confirmation and payment through GPay, PhonePe or Paytm, you receive the source code along with the report.
Frequently asked questions
What is RAG and why is it used in Generative AI projects?
RAG (retrieval-augmented generation) retrieves relevant text from your own documents and gives it to the LLM along with the question. This keeps answers relevant and reduces made-up responses.
Do Generative AI projects need an API key?
Many builds use a hosted LLM API, which needs an API key and internet access. Confirm the exact model setup with the ProjectNet team before ordering.
Can I demonstrate these projects on a normal laptop?
Yes. API-based projects run on a standard laptop with internet access. Running models locally needs more RAM.