How I Built an AI Sales Intelligence Dashboard in Python (With Code)

Before every sales call, I used to spend 45 minutes researching the prospect. Now my AI dashboard does it in 8 minutes — and the research is better. What It Does Feed it a company name and it returns: Company overview (size, revenue, industry, recent news) Key decision makers with LinkedIn profiles Technology stack analysis Competitor landscape 3 talking points tailored to their likely pain points Suggested pricing based on company size The Stack Python for the orchestration Claude API for analysis and synthesis Perplexity API for real-time web research Flask for the dashboard UI Core Implementation import anthropic import requests client = anthropic . Anthropic () def research_company ( company_name : str ) -> dict : """ Build a comprehensive research dossier on a company. """ # Step 1: Web research via Perplexity perplexity_resp = requests . post ( " https://api.perplexity.ai/chat/completions " , headers = { " Authorization " : f " Bearer { PERPLEXITY_KEY } " }, json = { " model " :