Local AI harness/workstation: local AI image editor, Ollama image generation routing, SDXL inpainting UI, CivitAI model imports, 8GB VRAM Stable Diffusion.

End-to-end offline OCR and semantic parsing pipeline for identity documents based on YOLOv11, PaddleOCR, and LLaMA-3.1.

A Claude Code skill for tiered model orchestration across configurable Advisor/Planner/Executor layers

ReHGNN is a deep learning framework for intelligent server recommendation in distributed large-model deployment scenarios.

A robust, modular, and production-ready platform for solar power system data analysis, machine learning, and prediction. Built with ZenML, Streamlit, MLflow, and a rich Python data science stack, this project enables end-to-end workflows from data ingestion and EDA to model training, deployment, inference and experiment tracking

Production RAG pipeline — grounded retrieval, source-cited answers, Precision@k + MRR eval. CLI + Flask REST API. Gemini · ChromaDB · Python 3.11+

🦾 MATA | Model-agnostic computer vision framework — detect, track, segment, classify, embed & more. One API for HuggingFace, ONNX, and TorchScript models. Built-in ByteTrack/BotSort tracking, ReID, VLM agent tool-calling, barcode decoding, and OCR evaluation. Zero-shot ready. 🚀

API engine for chaining image and video models into one durable workload.

Self-hosted model switcher for agents with profile-based provider accounts, encrypted credentials, OpenAI-compatible proxying, and per-agent manual model selection.

The MultiGen pathfinding model aims to predict a suitable model invocation path based on user input requirements, using known model information.

A production-ready, frugal, sovereign AI system that orchestrates India's open-source language models to achieve state-of-the-art reasoning on consumer hardware through Test-Time Compute (TTC) and Cognitive Serialization.

Semantic runtime above Citadel for raw language intake, context assembly, model orchestration, semantic journaling, reply publication, and restart-safe intent synthesis into structured policy decisions across the stack.

Build a reliable Retrieval-Augmented Generation pipeline that ingests documents, stores vectors, and generates grounded, source-cited answers.