scalable-ai
There are 0 repository under scalable-ai topic.
0xPlaygrounds / rig
⚙️🦀 Build modular and scalable LLM Applications in Rust
Language:Rust 4882MuhammadAinurR / crewai-playground
🚀 Build AI Agent Teams as Production-Ready APIs. Orchestrate CrewAI agents with FastAPI for enterprise-grade AI services. Leverage Groq's lightning-fast LLMs to deploy collaborative AI workflows at scale.
Language:Python 8sjsreehari / PyroScan-AI
PyroScan AI is a GenAI-powered multi-agent system for real-time forest fire prediction across 10 global zones. Designed for researchers and disaster teams, it includes agents for fire detection, weather analysis, and historical data mining. Deployable via CLI or Docker.
Language:Python 7InCoB / agentic-ai-agents-factory-orchestrator
Agentic AI Agents Factory Orchestrator modular, and asynchronous AI agent factory designed for AI-made dynamic workflow orchestration using LLM integration. Build scalable, agentic automation pipelines with robust error handling, plugin-based capabilities, a concurrent operations or outsource workflow building to Operator Agent.
Language:Python 4STiFLeR7 / MedMNIST-EdgeAI
MedMNIST-EdgeAI -> an end-to-end exploration into model distillation, optimization, and deployment for resource-constrained environments, all centered around the MedMNIST medical imaging dataset.
Language:Python 1Variable-Fox / ASAN-Architecture
ASAN: A conceptual architecture for a self-creating (autopoietic), energy-efficient, and governable multi-agent AI system.
B-Yassine88 / PathMNIST-XAI-Lightweight-Explainable-CNN-for-Medical-Imaging
🔍 Enhance medical imaging with a lightweight CNN model that offers over 91% accuracy and integrated explainability for better clinical trust.
Language:PythonManibalaSinha / ai-api
AI / Python / Backend Production-ready AI API service with prompt engineering, RAG readiness, caching, monitoring, backend architecture, and secure deployment.
Language:PythonShreyaVijaykumar / PathMNIST-XAI-Lightweight-Explainable-CNN-for-Medical-Imaging
A lightweight Explainable AI CNN for PathMNIST medical imaging, achieving 91%+ accuracy with Integrated Gradients and SQLite-based attribution storage. Built in PyTorch, this scalable model delivers high performance, transparency, and real-world readiness, making it ideal for medical AI, edge deployment, and explainable deep learning research.
Language:Python