Neurochat is an AI-powered meditation companion built on GPT-5, designed to make mindfulness truly personalized and accessible. Today’s meditation apps are static, offering generic tracks that ignore user context. Neurochat solves this by leveraging GPT-5’s advanced reasoning, large context capacity, and dynamic tool orchestration. Users can engage via chat, voice, or file uploads—including PDFs or HRV smartwatch data—for stress-aware meditation tailored to their needs. GPT-5 enables verbosity control, reasoning effort tuning, and parallel orchestration of the given tools. Targeting wellness seekers, therapists, and enterprises, Neurochat taps into the $100B+ global wellness industry. Its competitive edge lies in GPT-5’s ability to process up to ~400k tokens, generate structured multimodal outputs, and adapt in real time—features not seen in GPT predecessors. Neurochat demonstrates how advanced AI can transform meditation from static recordings into dynamic, research-backed, user-specific experiences.

This project explores the development of an AI-based quiz generation system using GPT-3.5 and Vectara to foster personalized and adaptive learning experience. Our methodology involved sourcing relevant structured dataset, data pre-processing, embeddings generation, vector database storage, hybrid-search retrieval, LLM feed, prompt engineering, and context-based response. The primary challenge addressed is the insufficient customization in quiz generation and overcoming the challenge of generating precise and contextually relevant quiz questions that minimize the risk of LLM generating incorrect or misleading information (hallucinations). We also have included an option for the user to upload their preferred document and let the app generate quiz. As the users answer the questions, the LLM will generate further questions adapting the difficulty level. The hallucination levels are found to be really low as per Vectara in-built evaluations. This is designed for interactive AI based user learning and is scalable to different arenas like education, online learning, and employee trainings.

ResearchWriterGPT is an Advanced Multimodal Research Paper Writing Assistant is a groundbreaking tool designed to transform academic writing. It harnesses the language and vision capabilities of GPT-4 to assist in crafting research papers, processing both textual and visual data to ensure thorough coverage from abstract to conclusion in APA format. The project showcases its multimodal capabilities, including image and chart scanning and analysis. It offers direct access to academic databases like Google Scholar, Semantic Scholar, Pubmed, etc., facilitating the literature review process by aggregating and filtering peer-reviewed information. Additionally, the tool enhances user experience through interactive dialogues, audio interaction, PDF analysis, and PPT downloading option. GPT-4 Vision expands the application's scope by enabling detailed image analysis, such as reading texts and interpreting charts from research photos and medical images. The integration of a Pinecone-based RAG system allows users to upload a collection of documents, which the system appends to for relevant response generation. This creates a vast knowledge base, potentially processing millions of articles for quick, contextually relevant responses, supporting efficient document management and advancing context-based AI LLM feed. TruLens further strengthens the tool by evaluating hallucinations in three key dimensions: context relevance, groundedness, and answer relevance. This ensures the LLM application is free from hallucinations, delivering accurate and relevant information. The Trulens leaderboard feature displays the relevancy score of the LLM responses giving realtime feedback. Future expansions aim to incorporate advanced models for face sentiment analysis and object detection, predictive bibliography features, and comprehensive writing support covering all aspects of a research paper.

ResearchWriterGPT: An Advanced Multimodal Research Paper Writing Assistant" is an innovative project designed to revolutionize academic writing. It combines the language and vision capabilities of GPT-4 with Clarifai's advanced AI tools to assist in drafting research papers. The tool is adept at processing both textual and visual data, ensuring comprehensive coverage from abstract creation to conclusion formulation, all in APA format. The project stands out for its integration of multimodal capabilities, including image and chart scanning, and analysis. It provides direct access to prominent academic databases like Google Scholar and Arxiv, streamlining the literature review process by aggregating and filtering relevant information. Furthermore, the tool enhances user experience by supporting interactive dialogues, including audio interaction, and allows for PDF analysis and conversion. Its innovative GPT-4 Vision feature broadens the application scope by enabling detailed image analysis, including reading texts and interpreting charts from various sources like research photos and medical images. In addition, the integration of Retrieval-Augmented Generation (RAG) with Clarifai creates a vast knowledge base, processing over 1.7 million STEM articles from ArXiv for quick, contextually relevant responses. This system not only supports efficient document management but also advances AI interaction for academic research. The technology backbone of ResearchWriterGPT includes GPT-4 Turbo for text generation, GPT-4 Vision for image processing, DALL-E API for image generation, and Clarifai’s RAG system for enriched data handling. Future expansions envision incorporating advanced Clarifai models for face sentiment analysis and object detection, predictive bibliography features, and comprehensive writing support covering all aspects of a research paper.

PsychGenGPT is an innovative solution for mental health support, blending AI with proven psychological practices to provide accessible and tailored assistance. It addresses the significant global economic impact of mental illness, estimated at $2.5 trillion, and the potential productivity loss of $16.3 trillion by 2030. The AI mental health market is rapidly growing, with a projected value of $59.18 billion by 2030. This platform is grounded in scientific research, showing the effectiveness of meditation in reducing stress and depression. PsychGenGPT employs a three-stage therapy approach: Emotional Processing, which includes techniques like mindful observation; Mental Processing, using approaches such as present-moment awareness; and Future Visualization, focusing on positive future envisioning. Core functions include active listening, user profiling, therapy script generation, and real-time interactive support. It also offers advanced analytics for session feedback and is designed for accessibility and cost-effectiveness. A unique feature is its text-to-speech psychotherapy sessions, enhancing user engagement. In short, PsychGenGPT is an AI-based mental health platform offering personalized, accessible, and cost-effective psychological support, combining innovative technology with traditional therapeutic techniques. This is not a diagnosis or professional advice but a sheer support for mental health symptoms management. PsychGenGPT employs a comprehensive three-stage therapy approach for smooth transitioning from negative emotions to stress to productivity. It generates a detailed therapeutic advice, psychotherapy script and an audio guided psychotherapy session.

With 15% of working-age adults facing mental disorders and an annual loss of US$ 1 trillion in the world due to impaired productivity from depression and anxiety, the necessity for real-time emotional and physiological monitoring is paramount. PsychGen, developed using AutoGen multi-agent platform, aims to democratize mental healthcare through AI-driven personalized psychotherapy sessions, addressing the global rise in mental health issues and the inaccessibility of traditional therapy. Utilizing a robust technology stack including AutoGen, Streamlit, OpenAI, AssemblyAI, Audiocraft, and DALL-E, PsychGen transitions seamlessly from text to audio, audio to music, and finally to video to enrich the therapeutic experience. The project encompasses multi-faceted agents such as a Psychological Chatbot for profiling and script generation, Speech and Music Generation for a meditative voice output and soothing soundtrack, Image and Video Generation for visual representation of therapy themes, and a Mixing agent for creating a comprehensive therapy session. PsychGen holds the promise of democratized access to psychotherapy, real-time personalized mental health support, and scalability for integration with other mental health resources, envisioning a future where quality mental healthcare transcends traditional barriers and is accessible to all.

ChatmanGPT revolutionizes development by automating code generation, aiding in rapid prototyping, and optimizing code based on AutoGPT. It's a comprehensive system builder with unique features like Prompt Matrix Innovation and real-time evaluation.

AISmartTask: Coded using Open-interpreter, AISmartTask is an innovative AI-driven task management solution tailored for coders or anyone who likes to manage daily routines. Leveraging the power of OpenAI's text engines, this tool is integrated with a Telegram bot, offering an intuitive user experience. Key features include dynamic task management that allows for task addition, prioritization, and AI-powered suggestions. Its document parser extracts essential summaries and highlights critical keywords. Additionally, AISmartTask visualizes task priorities, enabling users to get a clearer view of their tasks at hand. One standout quality is the tool's learning modules, which web scrape for knowledge, encouraging continuous learning. Users can interact with the system via intuitive Telegram commands (vocal or text) and provide feedback for continuous system improvement. With a modular Python architecture, AISmartTask is not just a task manager; it's a revolutionary tool aiming to optimize and enhance the daily routines of coders. It is scalable to any user and other applications such as enterprise project management, academic tasks management (students and educators), task management in healthcare, in the freelance and gig economy, or to manage tasks in any use cases.

Raga Music Generation Pipeline: RagaCraft Our project, RagaCraft, bridges the gap between raw human emotion and the timeless art of raga music using cutting-edge AI. Here's a deeper dive into the underlying process: Customer Interaction: Users interact with our platform, sharing their current emotions and contextual information. For example, "I am feeling romantic today. It is Valentine's Day. I'd like a song to suit the mood." JavaScript Selection: Our system, powered by JavaScript, scans the user's input to select an appropriate raga that resonates with the given emotion. OpenAI Integration: To add depth and specificity, RagaCraft sends a refined request to OpenAI: "Generate a text-to-music prompt for a single romantic raga. Include parameters such as tempo, scale, pitch, and rhythm to optimize the romantic mood. Define ideal values for these features." OpenAI's Response: The API, enriched with musical knowledge, replies with precise musical direction. For instance, "For a romantic setting, employ the Hindustani raga Kamboji. Utilize a medium-slow tempo, major scale, and a high pitch with low undertones. The rhythm should be gentle with a 4/4 signature. Dynamics can vary, with crescendos and decrescendos, ensuring a light texture and smooth timbre." Audiogen Transformation: The detailed prompt from OpenAI is fed into Audiogen, which processes it and crafts a song that encapsulates the user's emotions. Delivering the Experience: Our user interface then presents the generated raga song to the user, completing a journey from raw emotion to personalized musical expression. Through RagaCraft, we're redefining the way users experience and interact with traditional music forms in the age of AI.

Join our $1,000,000+ startup challenge series powered by Surge ⏱️ 8 days to turn your idea, or existing product, into an investable demo. 📅 February 6 - 15, 2026 • Feb 6 - 14 (Online Phase) - Collaborate and build online with developers and AI innovators from around the world. All projects must be submitted by the end of the online phase on February 14th. • Feb 14 (On‑site Build Day) - Selected participants will be invited to an exclusive in‑person session to refine their projects and connect directly with mentors. • Feb 15 (On‑site Demos & Awards) - Live pitching sessions to a panel of judges and ecosystem partners, followed by the official winner announcement. 🌟 Get feedback from startup mentors and technical experts. 📍 On-site Venue (Feb 14–15): MindsDB SF AI Collective 3154 17th St, San Francisco, California, USA 🤝 Join solo or with a team. New founders and existing startups are welcome. 🏆 $1,000,000+ in credits, token prizes, perks and funding opportunity. 📍 On-site participation is by invitation only. Travel and accommodation expenses will not be covered. 🧑‍💻 Apply now to build, validate, and pitch with purpose.

⌚ 3-day AI Hackathon 🚀 Compete to build an AI app powered by Llama 2 💡 Learn how to extend your capabilities with Clarifai! 🎓 Mentors are available to support you during your creative journey

🤖 You have 4 weeks to build. Join in at any point! 🌐 Connect with a global tech community. 🎉 Win from a $30,000 cash prize pool. 💾 The winning agent will become the AutoGPT in the 150000 star repository! 🚀 You may continue your startup journey after the Hackathon! 🖥️ Utilize Weaviate as the vector database for your agent with open access.

Introducing AudioCraft: Dive into the cutting-edge of audio processing and generation with deep learning! Empower your audio applications with AudioCraft for richer, more versatile soundscapes.