Devneet Mohanty

Built an end-to-end automated trade report aggregation and reconciliation system for a global asset management client. I integrated UiPath RPA with Python-based data transformation and Oracle fund mapping to process intraday broker feeds, auto-validate exceptions, and deliver consolidated outputs. I also implemented REFramework-based scalable architecture with robust error handling, logging standards, and nightly scheduled runs to reduce manual workload and improve control visibility.

Developed an enterprise automation pipeline for a hedge fund's invoice ingestion and attachment handling using UiPath. The solution included email parsing, AWD web portal scraping, metadata extraction, structured storage, and SLA tracking, eliminating repetitive manual processing and improving response times. I also integrated error classification and reporting dashboards.

Automated daily Slack message exports (from Production and Sandbox) into Proofpoint for archival, enabling audit readiness without reliance on enterprise APIs. I designed a solution using UiPath with structured exception handling, SLA monitoring, Okta SSO support, regional file routing, and exception alerts. I also improved the compliance posture and substantially reduced manual archival effort.

Designed and implemented an end-to-end Power BI analytics solution integrating EMW XML APIs, Google Sheets, UiPath Orchestrator APIs, and Google Forms feedback data. I built a structured data model with DAX KPIs (YTD letters, bot success rate, and partner performance metrics) and deployed dashboards to Power BI Service with scheduled refresh and alerting. I also enabled real-time visibility into 2,000+ engagement records, bot telemetry, and audit metrics, eliminating the need for daily manual exports and improving leadership decision-making.

Designed and deployed a cloud-based invoice triage system using Power Automate, Power Apps, and SharePoint as a lightweight data layer. I built automated flows to ingest invoices from Outlook, classify vendors using AI Builder and OpenAI, trigger multi-level approval workflows, and push structured data to downstream ERP systems. I also implemented exception handling, SLA timers, escalation rules, and adaptive approval notifications in Teams, reducing manual routing effort by 70% and improving approval cycle time by 40%.

Built an automated SLA monitoring framework using Power Automate cloud flows integrated with Outlook, SQL, and Azure services. I implemented time-based triggers, condition branching, and dynamic escalation rules to notify stakeholders when operational KPIs breached defined thresholds. I also integrated them with Power BI dashboards for real-time SLA visualization and compliance reporting, and enabled proactive issue management and reduced missed SLAs by 50%.