I’m a private equity investor building a lightweight internal tool to automate the first step of financial deal modeling. The goal is to upload typical M&A materials (e.g., CIMs, financial models, and market reports) and have AI extract key financial and operating data to pre-populate a financial model in Excel. This will be used for prototyping and internal testing only (not commercial SaaS yet). Key Deliverables 1. File Upload Interface - Simple web UI to upload PDF CIMs and Excel files (Streamlit or Flask) 2. AI-Powered Data Extraction - Use GPT API to extract: Revenue, EBITDA, CapEx, Purchase Price, Leverage, Exit Multiple, etc. - Output in JSON or Python dict 3. Excel Model Integration - Use a provided Excel LBO model template / or create one - Programmatically populate assumptions into the model - Generate a downloadable .xlsx file 4. Optional - Display extracted assumptions for manual review/edit before export - Highlight any missing inputs the user should fill in Budget is negotiable.
Keyword: Data Analysis
Price: $2.0
Python Streamlit GPT API LangChain
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