Automated Research and Reporting Agent

Problem

Analysts were spending forty hours a month manually monitoring regulatory updates, earnings transcripts, and sector news.

Solution

• Designed an agentic research pipeline that scrapes predefined sources every morning.
• Summarises changes using a domain-trained model.
• Flags anomalies using a scoring algorithm: Relevance score = (Keyword Weighting + Sentiment Shift + Event Type Weighting).
• Built a daily research report delivered into Slack, Outlook, and Notion.
• Created SOPs for integrating the agent into the research team workflow.

Outcome

• Cut weekly research time by seventy percent.
• Analysts spent time on client engagement rather than summarisation.
• Improved accuracy by eliminating manual oversight errors.