Building Encito's Investment Note Process: Dozens of One-Pagers Across Clean Energy
Developed and refined a repeatable framework for producing scannable, investor-ready one and two-pagers across clean energy sectors.
Aayush Bharti
Market Research Analyst at Encito Advisors
From their time as
Market Research Analyst
Encito Advisors • 2024
Overview
Across two years at Encito, Aayush produced dozens of investment notes and one-pagers covering companies and sectors across clean energy. The volume forced him to develop a repeatable, efficient process for turning raw data into structured, investor-ready outputs.
The Story
Across two years at Encito, Aayush produced dozens of investment notes and one-pagers covering companies and sectors across clean energy. The volume forced him to develop a repeatable, efficient process for turning raw data into structured, investor-ready outputs.
His starting point for any note is a time-boxed data collection phase. He pulls from pitch decks, company websites, LinkedIn, recent news, and any available industry reports, compiling everything into a single Excel file before beginning analysis. This prevents him from reading and re-reading sources; everything is in one place.
From there, he uses a combination of AI tools, including ChatGPT, Claude, Gemini, and Notebook LLM, to synthesize what the sources are saying. Notebook LLM in particular helps him visualize the content of dense articles, giving him a sense of the key themes before he begins structuring his output.
His output framework is consistent across every note: company overview, target market, traction, unit economics, financials, and a final section carrying his own analytical conclusion. The design principle is scannability: an investor or senior stakeholder should be able to extract the key numbers and business model in seconds.
He keeps outputs to one page where possible, two pages at most. The discipline of the format forces him to decide what actually matters and what to leave out.