A Multi-Agent Intelligence System | Built by Ali Seena
Your intelligent workspace powered by autonomous AI agents — where you can read, search, summarize, and communicate intelligently.
ALVEO AI is a multi-agent intelligence application built with Streamlit and orchestrated through the LangChain framework. It unites three specialized AI agents and a guide chatbot in one streamlined platform — creating a collaborative AI environment that performs document analysis, news summarization, and email automation with seamless user interaction.
Upload a PDF file and let NexaAI convert it into embeddings for semantic understanding. You can then chat with your document — ask complex questions, clarify unclear concepts, and get detailed analogies. If the answer isn't found within the document, NexaAI uses an integrated web search tool to find and deliver contextual answers from the internet.
Stay informed with the world’s trends. Enter any topic or domain, and NewsFlow AI searches for the most relevant and recent articles. It generates summaries and provides article links for reference. You can continue the conversation to discuss or analyze the updates. A built-in web search module ensures responses are always real-time and accurate.
Forget about filling out forms. Just describe your intent in natural language (e.g., “Send a formal apology email to John about the project delay”). AutoMail AI extracts details like sender, recipient, tone, and message context — and automatically generates a professional email draft. You can revise, edit, or approve before sending. Currently, the email agent sends messages from the developer’s address, but future updates will allow user-specific sender integration.
A built-in chatbot that helps you navigate, learn, and interact with the agents. It provides real-time guidance and support across all modules, making the experience smooth and user-friendly.
- Python Programming Language — The core foundation of the entire system.
- LangChain Framework — Used for orchestration of tools, agents, and LLM interactions.
- Streamlit Framework — For building the UI and front-end integration with the agents.
- Gemini Models — Core large language models powering reasoning, summarization, and response generation.
- Pinecone — Used for the RAG (Retrieval-Augmented Generation) system to manage embeddings and semantic search.
Additionally, several Python libraries were used to support features such as data handling, vector storage, API integration, and backend optimization — though they are not listed here individually.
Building ALVEO AI was an intense and valuable experience. Key learning highlights include:
- Mastering the LangChain framework for orchestrating LLMs and agents.
- Understanding data pipelines and flow management between multiple agents.
- Implementing RAG systems for document comprehension and knowledge retrieval.
- Working with Gemini APIs and managing model performance.
- Handling Streamlit UI integration and debugging API deployment issues.
The Email Agent was the most challenging part — extracting structured data from natural language took considerable experimentation. Integrating everything into a single functioning UI and managing secure API keys also required persistence and problem-solving. The entire project took about one month to build, combining both learning and development.
- Python — Core programming and logic
- Streamlit — Front-end user interface
- LangChain — Multi-agent and tool orchestration
- Gemini APIs — Model reasoning and responses
- Pinecone — Vector database for embeddings
- News APIs — For real-time article fetching
- 📄 Intelligent document Q&A system with PDF uploads
- 🌐 Integrated web search for real-time knowledge
- 📰 Automatic news summarization with article links
- ✉️ Natural language-based email generation and editing
- 🤖 Interactive chatbot for assistance and guidance
Ali Seena — Self-taught AI Engineer & Product Developer
Focused on building intelligent systems that automate workflows and bring AI closer to human usability.
Specialized in AI Agent Engineering and real-world applications of intelligent systems.
For collaborations, hiring, or inquiries — reach out via:
- Email: aliwork0066@gmail.com
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