Live platform Equity research

LeverageFutures.com

Long-form equity research with modular valuation tooling, Chart.js visuals, and Gemini-powered analyst support.

A multipage research platform that combines long-form company dossiers, interactive segment-based valuation models, and an AI-assisted analyst experience. The product is designed as a readable research surface first and a valuation tool second, so users can move from thesis to assumptions to model output without leaving the page.

Frontend HTML, CSS, vanilla JavaScript
Modeling Chart.js, tabbed calculators, model tables
AI Cloudflare Pages Functions, Gemini API

Platform premise

LeverageFutures.com is a data-driven investment research platform designed to help readers analyze high-growth companies through structured, segment-level research.

Rather than separating editorial writing from model outputs, the site combines long-form company dossiers, valuation appendices, and interactive tools in one product surface.

The result is a research workflow where readers can move from thesis framing and scenario logic to segment assumptions and implied value without switching platforms or downloading a separate spreadsheet.

Product features

The platform is built as a lightweight web product rather than a single calculator page. Key product features include:

  • Coverage landing pages that present active company dossiers across the research universe
  • Long-form company reports with thesis, scenario framing, and valuation appendices in one reading flow
  • Segment-level calculators that break revenue, margins, and EPS into explicit operating drivers
  • Standalone report surfaces and appendices for deeper company-specific analysis
  • An embedded AI analyst widget that can answer questions about assumptions, valuation logic, and risk framing

This makes the site feel closer to a continuously updated research product than a static blog or a single-purpose spreadsheet clone.

Tesla valuation model

Within the platform, the Tesla valuation page serves as a concrete example of the segment-based method. The model calculates Tesla's future EPS by breaking the business into major operating segments such as:

  • Automotive
  • Energy
  • Robotaxi and autonomous services
  • Optimus and emerging technologies

Each segment has its own revenue model, margin assumptions, and output that contribute to a consolidated EPS estimate.

The valuation UI is organized as a modular web interface with tabbed sections, calculator views, and report-style output so users can inspect both the inputs and the final implied valuation.

How it is built

  • A static multipage architecture built with hand-authored HTML, shared CSS, and vanilla JavaScript rather than a heavyweight frontend framework
  • Reusable site chrome through shared header and footer partials loaded by a lightweight include.js helper
  • Company-specific valuation pages composed from focused JavaScript modules such as auto.js, energy.js, robotaxi.js, and optimus.js
  • Supporting scripts handle scenario toggles, summary rollups, chart rendering, and chatbot mounting so each research surface stays modular instead of monolithic
  • Client-side calculation flows that keep assumptions transparent and make scenario edits feel immediate

Tech stack

The underlying repo is intentionally lightweight, but the stack is explicit and purpose-built for research publishing, interactive valuation work, and AI-assisted reading.

Layer Verified stack
Frontend Hand-authored HTML, shared CSS, and vanilla JavaScript
Architecture Static multipage structure with shared header and footer partials loaded via include.js
Modeling Company-specific valuation modules such as auto.js, energy.js, robotaxi.js, optimus.js, plus related scenario scripts
Visualization & UX Chart.js charts, tabbed calculator surfaces, scrollable financial tables, and accessibility-focused tab and input labeling
AI backend /api/gemini implemented with Cloudflare Pages Functions, env-managed GEMINI_API_KEY, Gemini model routing, and a shared stock chatbot widget
SEO & distribution Canonical URLs, Open Graph and Twitter tags, JSON-LD structured data, sitemap, and web manifest

Interactive tooling and backend support

The site is mostly static, but it still supports richer product behavior where it matters.

  • A shared stock chatbot widget can be mounted across valuation pages and fed company-specific context
  • The /api/gemini function proxies Gemini with env-managed secrets, allowed-model routing, message and prompt limits, and response continuation when output is truncated
  • Chart-backed views, scrollable table containers, and tabbed sections make dense valuation models usable on smaller screens without losing structure
  • Accessibility helpers add keyboard-friendly tab behavior and more explicit labels for calculator inputs embedded inside large financial tables

This combination keeps the product fast and easy to maintain while still supporting AI-assisted workflows and reusable analytical components.

Future plans

  • Expand the coverage universe with more company dossiers and sector-specific model templates
  • Add richer scenario comparison, exportable model views, and more reusable appendix patterns
  • Keep evolving the AI layer so readers can interrogate assumptions while reading the reports

Leverage Futures aims to make valuation more understandable, structured, and grounded in real business economics while still feeling like a focused, readable web product.