SuperCoder 2.0: An advanced autonomous system designed to enhance software development through artificial intelligence. Key focus areas include a retry mechanism with error output trace back, comprehensive code rewriting and replacement using Abstract Syntax Tree (ast) parsing to minimize linting issues, code embedding technique for retrieval-augmented generation, and a focus on localizing methods for problem-solving rather than identifying specific line numbers.V-Zen: Advancing Robotic Process Automation (RPA) with State-of-the-Art Multimodal LLM: The model is proficient in designing logos and posters, catering to diverse design needs with finesse and efficiency using Canva. It seamlessly interacts with Gmail and Calendar, enabling tasks such as composing, reading, and replying to emails, as well as scheduling and modifying meetings with ease and accuracy.V-Zen outperforms GPT-4V, Gemini Pro and other SOTA models in grounding for the GUI tasks. GUIDE dataset was used for training the V-Zen.V-eagle: Multimodal LLM used for advancements in Multimodal Representation: Introduced an Open-source vision model that beats SOTA models like BLIVA, Instruct-BLIP, mPlug-Owl & LLAVA in major benchmarks due to its unique architecture, highly optimized datasets, and integrations.Created the entire model dataset from scratch by pre-processing all the open source datasets.GUIDE: Graphical User Interface Data for Execution: A novel dataset tailored for the advancement of Multimodal Large Language Model (MLLM) applications, particularly focusing on Robotic Process Automation (RPA) use cases. Dataset encompasses diverse data from various websitesincluding Apollo(62.67%), Gmail(3.43%), Calendar(10.98%) and Canva(22.92%).