QuantumEdge

QuantumEdge is a production-oriented optimization platform for small and mid-sized UK investment banks. It helps treasury teams, portfolio managers, and advisory desks compare classical baselines against quantum-ready optimization workflows for portfolio construction, rebalancing, treasury allocation, and trade basket selection.

Positioning

QuantumEdge sells business outcomes, not quantum hype.

It is built to answer questions like:

• can we improve allocation quality versus a classical baseline?
• can we reduce turnover or capital friction under realistic constraints?
• can we prepare today on simulators and hybrid solvers before moving to hardware-backed workflows later?

What users see

QuantumEdge is meant to produce output that is easy to read, not just technically correct.

Every optimization run should surface:

• baseline vs optimized expected return
• risk change
• budget utilization
• turnover impact
• constraint status
• annualized gain estimate
• allocation changes by asset
• plain-English explanation of what changed and why

Example result summary

Scenario: Boutique Wealth Desk
Solver mode: Hybrid

Baseline portfolio
- Expected return: 10.9%
- Variance proxy: 8.1%
- Turnover: 19%
- Constraint violations: 1

Optimized portfolio
- Expected return: 12.3%
- Variance proxy: 7.1%
- Turnover: 12%
- Constraint violations: 0
- Budget usage: 99.8%

Business impact
- Estimated annualized gain: £185,000
- Risk posture: improved
- Compliance status: constraints satisfied

Allocation changes
- UK_GILT_5Y: 25% -> 30%
- FTSE_BANKS_BASKET: 20% -> 25%
- GBP_LIQUIDITY: 25% -> 20%
- MIDCAP_ALPHA: 30% -> 25%

Plain-English explanation
The optimized allocation improved expected return while reducing the risk proxy and turnover.
This run stayed within the configured budget and liquidity constraints.
The workflow remains simulator-first / hybrid-ready, so the same business logic can later target D-Wave-backed execution through the adapter layer.

That output philosophy is intentional: the machine-readable payload is for integrations, but the README and product should already show the human-readable layer that analysts and decision-makers will actually consume.

Monorepo layout

• apps/web , analyst-facing web app
• services/rust-api , auth, workspace, jobs, audit, orchestration API
• services/python-optimizer , optimization engine with simulator and hybrid adapters
• packages/shared-schemas , shared API and scenario schemas
• examples , sample datasets and demo scenarios
• docs , architecture, onboarding, and API docs

Requirements

• Python 3.11+
• Rust stable toolchain
• Node.js 22+
• npm
• Git

Quick start

1. Clone the repo

git clone https://github.com/yablokolabs/quantumedge.git
cd quantumedge

2. Bootstrap dependencies

./scripts/bootstrap.sh

This script will:

• create the Python virtual environment
• install Python dependencies
• run cargo check for the Rust API
• install npm packages for the web app
• build the web app once

Run the project locally

Terminal 1, start the Python optimizer

cd services/python-optimizer
source .venv/bin/activate
uvicorn quantumedge_optimizer.main:app --host 0.0.0.0 --port 8099 --reload

Terminal 2, start the Rust API

cd services/rust-api
OPTIMIZER_URL=http://127.0.0.1:8099 cargo run

The Rust API will start on:

• http://127.0.0.1:8098

Terminal 3, start the web app

cd apps/web
npm run dev -- --host 0.0.0.0 --port 5173

The web app will start on:

• http://127.0.0.1:5173

Run with Docker Compose

docker compose up --build

This starts:

• Rust API on http://127.0.0.1:8098
• Python optimizer on http://127.0.0.1:8099

Test the backend quickly

Health check

curl http://127.0.0.1:8099/health

List templates

curl http://127.0.0.1:8098/templates

Create an optimization job

curl -X POST http://127.0.0.1:8098/jobs/optimize \
  -H 'Content-Type: application/json' \
  -d '{
    "template": "boutique-wealth-desk",
    "solver_mode": "hybrid",
    "annual_capital_gbp": 25000000
  }'

Upload a CSV file

curl -X POST http://127.0.0.1:8098/uploads/csv \
  -F 'file=@examples/boutique-wealth-desk.csv'

Current state

This repo contains a runnable local demo scaffold with:

• simulator-first optimization workflows
• Rust API endpoints for scenarios, jobs, results, templates, and CSV upload scaffold
• frontend shell for scenario building and result comparisons
• shared schemas and example datasets
• CI workflow and local bootstrap support

Key docs

• docs/onboarding-analysts.md
• docs/onboarding-quants.md
• docs/onboarding-developers.md
• docs/architecture.md
• docs/api.md