This Langflow flow creates an AI assistant that automatically prepares sales meeting briefings by analyzing calendar events and researching attendee companies. The system uses an OpenAI-powered agent that receives detailed instructions through a prompt component, which tells it to read calendar events, extract participant email domains, and research associated companies. The agent has access to two main tools: a Google Calendar integration for retrieving meeting information and a Serp Search API for conducting web research on companies.

The workflow begins when the agent receives the system prompt containing comprehensive instructions for meeting preparation. The prompt specifies that the agent should analyze event titles, descriptions, and participant lists from the connected calendar, then extract email domains to identify companies that need research. The agent is instructed to gather specific information about each company including their value proposition, industry sector, company size, main products, and target customers using credible web sources.

The agent processes this information and delivers structured output for each calendar event, providing actionable business context in 3-5 line summaries. It maps participants to their associated companies, suggests 2-3 relevant talking points for sales or partnership conversations, and includes source links for verification. The system maintains professional standards by only using verifiable information and clearly stating when data is insufficient, ensuring the sales team receives reliable intelligence for their upcoming meetings.

The flow can be extended using other Langflow nodes to create more comprehensive meeting preparation. You could add vector store retrievers to pull internal CRM notes and previous meeting records, incorporate API request components to fetch data from sales tools like Salesforce or HubSpot, or use structured output components to format briefings as standardized templates. Additional Composio integrations could automatically update calendar descriptions with research findings or send briefings to Slack channels, while agent components could enable more sophisticated reasoning about meeting priorities and research depth based on deal size or relationship status.