Apps Intellect

02/07/2026

Airline make million-dollar capital decisions every quarter 鈥� fleet orders, fuel hedges, route investments 鈥� often from spreadsheets that can't tell them what's actually optimal under real constraints.
Built Financial Planning & Analysis platform - FlyOpsHQ FP&A to change that

馃搱 10-page Streamlit frontend (desktop 路 tablet 路 mobile)

馃搳 FP&A Dashboard,
馃椇 Route P&L Intelligence,
馃捄 Revenue Optimizer,
馃挵 Cost Portfolio Optimizer,
鉀� Fuel Hedging Optimizer,
鉁� CapEx Portfolio Optimizer,
馃搱 Budget vs Actuals,
馃搲 Financial Plans & Forecast,
馃敡 KPI Analytics,
馃梽 Database & Audit

馃 4 Google OR-Tools CP-SAT optimization models running simultaneously

Live demo: https://financials.appsintellect.org/

10 financial intelligence pages covering Revenue, Cost, Fuel Hedging, CapEx, Budget vs Actuals, Forecasting, and KPI Analytics. Powered by Google OR-Tools CP-SAT.

25/06/2026

Airlines lose millions every year not because they lack data 鈥� but because competitive intelligence arrives too late and in the wrong format for decision-makers to act on.
Just shipped 鈥� FlyopsHQ CI Radar, a full-stack Competitive Intelligence platform for airline route strategy.
Here's what's under the hood:
馃摗 11-page Streamlit frontend (desktop 路 tablet 路 mobile)
馃 4 Google OR-Tools CP-SAT optimization models running simultaneously
馃梽 PostgreSQL 16 backend with 6 CI tables and fare history records
馃惓 Dockerised 3-container stack (Postgres 路 Streamlit 路 Nginx) with TLS
馃搳 Per-page Excel exports with severity color-coding and auto-filter
Every page follows the same pattern: configure parameters 鈫� click Run 鈫� results render 鈫� Download Excel activates.
Built with: Python 路 Streamlit 路 OR-Tools CP-SAT 路 PostgreSQL 路 openpyxl 路 Docker 路 Nginx
Live Demo: https://routes.appsintellect.org/

21/05/2026

✈️ Introducing AirHedge Suite — a purpose-built treasury risk management platform for airlines.

Airline treasury teams face a unique triple threat every day: jet fuel prices swinging with Brent crude, multi-currency revenue streams exposed to volatile FX markets, and complex debt portfolios denominated in foreign currencies. Most tools weren't built for this. We built one that was.

🔷 What AirHedge Suite does:

✅ 3-Layer Hedge Optimizer — Runs deterministic, stochastic, and portfolio-combined CP-SAT optimization (powered by Google OR-Tools) to find optimal fuel + FX hedge schedules across tenors — in seconds, not spreadsheets.

✅ Revenue at Risk (RaR) Engine — Monte Carlo simulation across 3,000+ scenarios to quantify revenue exposure by route, currency, and yield shock. Includes break-even load factor analysis and hedge effectiveness testing.

✅ Multi-Currency FX Engine — Manages exposures across EUR, GBP, JPY, AUD, SGD and more, with natural hedge netting, forward curve pricing, and VaR/CVaR reporting.

✅ Debt & Liquidity Manager — Full debt register, service calendars, refinancing cliff detection, and a CP-SAT optimizer that recommends ECB/USPP/Green Bond laddering to minimize interest cost and concentration risk.

✅ Crack Spread Optimizer — Models jet fuel refining margins and hedges crack spread exposure independently from Brent price risk.

✅ SSIM Schedule Integration — Connects flight schedules (SSIM format) directly to exposure calculations, so hedges reflect actual capacity.

Built on FastAPI + PostgreSQL + OR-Tools, with a Streamlit frontend deployed at treasury.appsintellect.org.

If you're a treasury professional, CFO, or risk officer at an airline and want to see what intelligent, solver-driven hedging looks like — Live Demo: https://treasury.appsintellect.org/

20 dashboards covering fuel hedging, FX exposure, CP-SAT optimization, debt & liquidity, and IFRS 9 hedge accounting.

26/03/2026

🚀 Introducing FlyOpsHQ — An AI-Powered Airline Operations Optimizer Built on Google OR-Tools CP-SAT
After months of deep engineering work, I'm excited to share FlyOpsHQ — a full-stack airline crew and tail optimization platform built using Google OR-Tools CP-SAT, Django, and Streamlit.

The Problem
Airlines lose millions daily from suboptimal crew scheduling, tail assignment inefficiencies, and slow disruption recovery.

What We Built
FlyOpsHQ runs a 4-stage unified optimization pipeline:
✈️ Stage 1 — Pairing Generation using column generation with DFS pricing. Produces legally valid crew pairings with strict rest enforcement and grey-zone elimination.
🔄 Stage 1.5 — Rotation Builder using CP-SAT to build continuous tail rotations respecting turnaround minimums.
🛩 Stage 2 — Tail Assignment solving a fleet assignment model with fuel cost optimization using live EIA jet fuel pricing.
👨‍✈️ Stage 3 — Crew Assignment using hub-isolated CP-SAT with a 2-pass post-solve verification system. Zero rest violations across all 5 Indian hubs (DEL, BOM, BLR, HYD, MAA) & multi-flights duties

Disruption Recovery
A window-based local recovery optimizer handles disruption event types — DELAY, CANCELLATION, AOG, MAINTENANCE, CREW_UNAVAILABLE, and AIRPORT_CLOSURE — using a ±6h CP-SAT window to protect 8GB RAM on constrained infrastructure. Processes 250 disruption events across 1,000 flights in under 15 seconds.

The Stack
🧠 Optimizer: Google OR-Tools CP-SAT + GLOP
🔧 Backend: Django REST Framework + PostgreSQL
📊 Frontend: 10 Streamlit dashboards — Crew Roster, Tail Rotation, Turnaround, Aircraft Utilization, KPI, Network Map, Disruption Recovery, and more

📁 Export: Full Excel exports with colour-coded disruption highlighting across all dashboards

By the Numbers
3 days schedule · 1,000 flights · 71 aircraft · 5 hubs · 1,134 crew
314 pairings
250 disruption events resolved & optimally assigned

Live Demo at https://flights.appsintellect.org/

-Tools

With AI-driven scheduling