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The most complete offline financial analysis desktop app.
9 Engines · ARIMA · GARCH · VaR · Monte Carlo · Black-Scholes · Markowitz · AI Copilot · OCR · TSETMC

Download · Live Demo · Quick Start · Issues


Why FinSight Pro?

Most financial analysis tools are either cloud-based (data leaves your machine), limited to one function (just ratios, just prediction), or require expensive subscriptions. FinSight Pro is the first and only tool that combines 9 specialized analysis engines — including quantitative finance — in a single offline desktop application.

  FinSight Pro Excel Online Tools Python Libraries
17+ Financial Ratios ✗ Manual ✓ Limited ✓ Code required
AI Copilot (EN + FA)
Bankruptcy Prediction 5 models 1-2 models ✓ Manual
OCR Document Extraction ✓ Code required
Industry Benchmarking 8 industries
IFRS + Iran Compliance 12+ checks
Consolidation Engine ✓ Code required
TSETMC Integration Some
ARIMA/GARCH Forecasting ✓ Code required
VaR / Monte Carlo / BS ✓ Code required
Portfolio Optimization ✓ Code required
100% Offline
Privacy / No Cloud
No Subscription
Visual Dashboard ✓ Basic
PDF/Excel Reports Some ✓ Code required
Multi-Language (EN/FA/AR)

Screenshots

📸 Screenshots coming soon — check the live demo for a preview!


9 Analysis Engines

1. Ratio Analysis

17+ financial ratios across 4 categories with color-coded status classification (Good / Warning / Critical):

Category Ratios
Profitability Gross Margin, Net Margin, Operating Margin, ROA, ROE
Liquidity Current Ratio, Quick Ratio, Cash Ratio, Working Capital
Leverage Debt-to-Equity, Debt-to-Assets, Interest Coverage, Equity Multiplier
Efficiency Asset Turnover, Inventory Turnover, Receivables Turnover, DSO

2. AI Financial Copilot

  • Dual-mode: Built-in rule-based engine (offline, EN/FA) + connect any LLM
  • Providers: OpenAI, DeepSeek, Ollama, OpenRouter
  • Context-aware: Automatically analyzes your uploaded financial data
  • Smart suggestions: Quick-start prompts for common financial queries

3. Bankruptcy Prediction

5 statistical models with consensus scoring:

Model Type Best For
Altman Z-Score (1968) Linear Public manufacturing companies
Altman Z-Score (1983) Linear Private companies
Springate (1978) Linear Canadian/public firms
Ohlson O-Score (1980) Logistic Probability estimation
Grover (2001) Linear General purpose

All models produce a consensus probability with zone classification (Safe / Grey / Distress) and actionable recommendations.

4. Document Intelligence (OCR)

  • PDF: Native text extraction + fallback OCR for scanned documents
  • Images: PNG, JPG, TIFF, BMP with Persian + English OCR
  • Excel: Multi-sheet smart extraction with header detection
  • Text paste: Direct text input with 70+ financial term mappings (EN ↔ FA)
  • Quality scoring: Completeness, balance sheet validation, field analysis

5. Industry Benchmarking

Compare against 8 industry profiles with real percentile rankings:

Technology, Manufacturing, Retail, Banking, Pharmaceutical, Oil & Gas, Real Estate, Food & Beverage

Includes auto-detection based on company name and ratio profile.

6. Compliance Engine

Automated checks against 12+ standards:

  • IAS 1, 2, 7, 16, 36 — Presentation, Inventories, Cash Flows, PPE, Impairment
  • IFRS 9, 15, 16 — Financial Instruments, Revenue, Leases
  • Iran-specific: VAT Law (9%), Corporate Tax (25%), Audit requirements, Social Security

Produces a compliance score (0-100%) with prioritized recommendations.

7. Consolidation Engine

  • Multi-company aggregation with ownership percentages
  • Automatic intercompany elimination entries
  • Minority interest calculation for <100% owned subsidiaries
  • Full consolidated ratio analysis (profitability, liquidity, leverage, efficiency)

8. Time Series Analysis

  • ARIMA(5,1,0) — Price forecasting with confidence intervals, auto-tuned AIC/BIC
  • GARCH(1,1) — Conditional volatility modeling, persistence analysis, volatility clustering detection
  • Decomposition — Trend, seasonal, and residual component extraction
  • Full pipeline — One-click analysis with summary statistics + actionable recommendations

9. Financial Engineering

  • Value at Risk (VaR/CVaR) — 3 methods: Historical, Parametric, Cornish-Fisher
  • Monte Carlo Simulation — Geometric Brownian Motion with 10,000+ paths
  • Black-Scholes — Option pricing with Greeks (Delta, Gamma, Vega, Theta)
  • Markowitz Optimization — Sharpe ratio maximization + minimum variance portfolio

+ TSETMC Live Market

  • Search any stock on Tehran Stock Exchange by Persian symbol
  • Real-time: Price, change %, volume, market cap, EPS, P/E ratio
  • Market overview with index data and popular stocks grid

Download

Format Link Size
NSIS Installer (.exe) Download Latest ~80 MB
Portable (.exe, no install) Download Latest ~70 MB
CLI (pip, MIT) pip install finsight-pro

Requires Windows 10/11 (64-bit). No .NET, no Java, no other dependencies.


App Overview

+--------------------------------------------------------------+
|  FinSight Pro                        [PRO] [API] [Min Max X] |
+------+-------------------------------------------------------+
|      |  Dashboard                                               |
|  D   |  +-------+ +-------+ +-------+ +-------+ +-------+     |
|  a   |  |  3    | |  17   | |  AI   | |  5    | |  Doc  |     |
|  s   |  |Anlys  | | Ratios| |  Bot  | | Pred  | | Intel |     |
|  h   |  +-------+ +-------+ +-------+ +-------+ +-------+     |
|  b   |  +-------+ +-------+ +-------+ +-------+ +-------+     |
|  o   |  |Bnchmrk| |Complnc| |Consol | | TSETMC| |Reprts|     |
|  a   |  +-------+ +-------+ +-------+ +-------+ +-------+     |
|  r   |  +-- Quick Analysis --------------------------------+   |
|  d   |  |  Drop CSV / XLSX / PDF / Image                    |   |
|      |  +---------------------------------------------------+   |
|  S   |  +-- Recent Analyses --------------------------------+   |
|  e   |  |  Acme Corporation    FY 2024  78%                   |   |
|  t   |  |  GlobalTech          Q3 2024  65%                   |   |
|  t   |  +---------------------------------------------------+   |
|  i   |                                                        |
|  n   |                                                        |
|  g   |                                                        |
|  s   |                                                        |
+------+-------------------------------------------------------+

Tech Stack

Layer Technology
Desktop Shell Electron 32 (Chromium, Node.js 22)
UI Framework React 18 + TypeScript 5.5
Styling Tailwind CSS 3.4 + Cascade Design System
State Management Zustand 4.5
Charts Recharts 2.15 (Bar, Radar)
Icons Lucide React
UI Primitives Radix UI
Backend API FastAPI 0.115 + Uvicorn
Database SQLAlchemy 2.0 + SQLite
PDF Generation ReportLab 4.2
OCR Tesseract (Persian + English)
Web Scraping BeautifulSoup + httpx
Build Vite 5.4 + electron-builder (NSIS + Portable)
CI/CD GitHub Actions (CI + Release)

Quick Start

# Clone the repository
git clone https://github.com/Ali-Marandi/finsight-pro.git
cd finsight-pro

# --- Frontend + Electron (Desktop App) ---
cd desktop
npm install
npm run electron:dev          # Full dev mode with hot reload

# --- Backend API only ---
cd api
pip install -r requirements.txt
uvicorn app.main:app --reload --port 8000

# --- Production Build ---
cd desktop
npm run electron:build:win    # NSIS + Portable EXE

Project Structure

finsight-pro/
+-- desktop/                  # Electron + React desktop app
|   +-- electron/             #   Main process + preload
|   +-- src/renderer/         #   12 pages, components, hooks, lib
|   +-- electron-builder.yml  #   NSIS + Portable config
+-- api/                      # FastAPI backend
|   +-- app/
|       +-- routers/          #   10 API router modules
|       +-- services/         #   10 service modules
|       +-- models/           #   SQLAlchemy ORM, Pydantic v2
|       +-- middleware/       #   License validation
+-- src/finsight/              # Core CLI engine (MIT)
+-- landing/                  # GitHub Pages landing page
+-- docs/                     # Architecture, API spec, brand
+-- .github/workflows/        # CI + Release workflows
+-- tests/                    # Test suite

CI/CD

Workflow Trigger What it does
CI Push / PR Python tests, TypeScript check, Vite build, ruff lint
Release Tag v* Windows NSIS + Portable, auto-publish to GitHub Releases
# Create a release (triggers GitHub Actions automatically)
git tag v0.4.0
git push origin v0.4.0

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License


Built with precision by Ali Marandi
If you find this useful, please give it a ⭐!

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AI-Powered Financial Analysis Desktop App — 7 Engines, 17+ Ratios, Bankruptcy Prediction, TSETMC Live, 100% Offline

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