AI Agent Designer Projects in Rohtak

AI Agent Designer Projects in RohtakAI Agent Designer Projects in Rohtak

Cover image for Healthcare AI-Based Decision Support System
Architected

Healthcare AI-Based Decision Support System Architected a multi-step LLM-powered clinical decision support platform that transforms patient records and medical guidelines into structured diagnostic workflows. The system combines OCR processing, patient-data ingestion, AI-powered reasoning, and human-in-the-loop validation to improve reliability and consistency of clinical recommendations. Key contributions included: • Designing the LLM decision-engine architecture • Building medical guideline-to-decision-tree workflows • Developing evaluation and review tooling for quality assurance • Integrating OCR and patient-data processing pipelines • Supporting orchestration across multiple AI and healthcare system components Technologies: Python, LLMs, OCR, Workflow Orchestration, Healthcare AI

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Cover image for Why do 70% of clinic

Why do 70% of clinic appointments fail? It’s not the medicine—it’s the management. Most doctors spend more time on paperwork than on patients. I built Ray Healthcare to flip that script. By integrating AI-driven scheduling and automated EMR (Electronic Medical Records), we’ve helped clinics reduce "no-shows" by nearly 70% while digitizing the entire patient journey. Key Features of Ray: ✨ Automated Smart Reminders: Turn-by-turn directions and instant SMS alerts. 🔒 HIPAA-Compliant Security: 256-bit encryption for total patient data privacy. 🚀 1-Click Billing: From prescription to invoice in seconds. Healthcare shouldn't be complicated. It should be digital.

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Cover image for AgentOS : Multi-Agent AI Orchestration

AgentOS : Multi-Agent AI Orchestration Platform Built AgentOS, a production-ready multi-agent orchestration platform that enables teams to deploy, monitor, and coordinate AI agents for complex workflows. Designed a modular architecture where specialized agents collaborate - handling tasks like research, code generation, and decision-making in parallel. Implemented real-time agent communication, persistent memory, tool-use pipelines, and a dashboard for observability. The system reduces manual intervention in repetitive workflows by over 80% and scales seamlessly across different LLM providers.

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