Build a production-ready Retrieval-Augmented Generation (RAG) pipeline with advanced features such as hybrid search (vector + keyword), multi-turn conversation memory, and enterprise-level authentication for accurate knowledge retrieval.

Develop a multi-agent collaboration platform where specialized agents (planner, researcher, executor, validator) work together to solve complex problems like code generation, code debugging, or business workflows.

Train a specific domain (finance, healthcare, legal, or education) and fine-tune a foundation LLM for domain-specific tasks like text classification or compliance checks, then deploy it with APIs.

Create a coding productivity tool with features like chat, complex code debugging suggestions, text generation, and inline documentation powered by LLMs and real-time developer context.

Design an app that combines text, images, and audio - e.g., generate presentations from text prompts, create an audio (podcast) with voice clones, or build an “AI lecture companion” with slides + narration.

Integrate graph databases with LLMs to build an intelligent assistant capable of reasoning over structured + unstructured data. Use cases: enterprise knowledge search, fraud detection, or academic research aid.

Build a pipeline manager for GenAI tasks (e.g., multi-step reasoning, summarization + action recommendation). Include monitoring, error recovery, and human-in-the-loop validation.

Develop an AI-powered BI tool where users ask natural-language questions and get interactive charts, summaries, and predictive insights automatically generated.

Create a tool to generate domain-specific synthetic datasets (textual and multimodal) for model training while preserving privacy and handling data imbalance issues.

Build an end-to-end content creation studio for dynamic content, SEO optimization, image generation, and auto-publishing. Extend with personalization for different target audiences.