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This two-agent system automates HR onboarding and finance expense processing. The HR agent collects new recruit details name, start date, hiring manager, and emails then sends onboarding emails, generates a checklist, creates a Google Calendar meeting, and shares the link with all participants. The Finance agent reads a mock expense database containing date, amount, and submitter, analyzes each expense, updates the database with an approve decline escalate status, and sends notification emails to the manager. Together, they deliver fast, accurate, and end-to-end automation for HR and finance operations.
23 Nov 2025
The SME Loan Risk Meta-Validator is an end-to-end intelligent workflow designed to streamline and modernize SME credit assessment. It automatically ingests loan applications from spreadsheets, portals, and supporting documents, then extracts and normalizes key information using OCR and AI-driven field extraction. The system enriches each application with external credit bureau and sanctions screening data, evaluates data quality and consistency, and applies transparent rule-based checks to enforce lending policies. For eligible cases, an AI risk model produces nuanced risk and eligibility scores, which are combined with rules to determine whether to auto-approve, auto-reject, or escalate for human review. An agentic policy reviewer ensures alignment with credit policies, fairness guidelines, and regulatory expectations. Every application generates a complete audit artifact—including inputs, risk reasoning, rules fired, and review actions—providing full traceability for risk teams and regulators. This workflow improves decision accuracy, reduces manual workload, ensures compliance, and delivers a scalable, consistent framework for SME lending.
19 Nov 2025
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