Chirag Singh

Overview Key Highlights

Developed an end-to-end AI-powered negotiation agent for RFQ workflows that automatically interprets vendor responses, scores offers, recommends negotiation tactics, and integrates actions into the procurement system via UiPath and SAP.

• Deployed an Agentic AI framework using LangChain to simulate negotiation steps: evaluation → counter-offer → escalation → contract draft.
• Integrated Azure OpenAI with vendor response data, enabling contextual and cost-aware offer scoring.
• Used UiPath bots to extract quote data, trigger counter-response emails, and update SAP PO drafts automatically.
• Implemented a feedback loop with sourcing managers to fine-tune prompt logic and negotiation tone based on deal history.
• Resulted in 30% higher savings per RFQ cycle and significantly reduced time-to-contract.

• Built a UiPath solution to read and extract fields from email-based Purchase Orders and post into SAP.
• Handled 80% of incoming PO workload autonomously.

• Created UiPath bots to aggregate production shift reports from Excel to Power BI dashboards.
• Saved 2+ hours daily of manual consolidation work.

• Automated inbound patient referral forms — scanned PDFs, extracted fields, verified insurance, updated hospital CRM using UiPath.
• Reduced referral cycle time from 3 days to same day.

• Used UiPath Document Understanding to scan supplier contracts and extract risk clauses.
• Routed flagged items via UiPath + Outlook integrations to legal reviewers.
• Cut contract approval cycle time by 60%.

• Developed a real-time agentic assistant using LangChain + Azure GPT to help factory workers resolve defect issues using SOP documents.
• Enabled natural language access to troubleshooting guides and tribal knowledge, reducing production downtime significantly.

• Built a summarization agent using Azure OpenAI + Azure Health Bot to convert clinical notes into structured summaries.
• Integrated with EHR systems to support discharge automation.
• Resulted in a 40% boost in clinical documentation speed and accuracy.

• Designed an LLM-based agent using Azure OpenAI + Form Recognizer to assess vendor eligibility from RFQ submissions.
• Automatically extracted and validated financials, ISO certs, and project histories for shortlisting.
• Result: Reduced evaluation time by 55% and enhanced audit trail.