driftcurve
driftcurve is a free, open-source retirement planning engine for modeling household finances and exploring retirement outcomes.
What driftcurve is
driftcurve is a free, open-source retirement planning engine for modeling household finances and exploring retirement outcomes. It accepts information for multiple household members, account types, debts, mortgages, pensions, Social Security, and property sales. Its default Monte Carlo simulations resample annual market data from 1966–2024, covering equities, Treasuries, residential real estate, inflation, and Bitcoin. Users can adjust historical returns toward their own long-run targets or choose static annual assumptions. Risk-based spending guardrails calculate monthly spending and suggest adjustments based on portfolio thresholds and probability of success. A Compare page displays two scenarios on one chart. In default local mode, household data and saved scenarios stay in browser localStorage, while forecasts run through a Python backend. Optional multi-user mode adds email/password accounts, server-side sessions, and stored profiles and scenarios. Setup uses a Python virtual environment, installs requirements, runs the app with Uvicorn, and opens it at localhost:8000. Guardrails require a retirement year and positive liquid portfolio, and the README says a computation takes about 20–45 seconds. The maker describes the tool as educational, not financial, investment, tax, or legal advice.
Good
- Models multiple household members and account types.
- Includes Social Security, pensions, mortgages, and property sales.
- Compares two scenarios on one chart.
- Open source under the Apache License 2.0.
Watch out
- Guardrails require a retirement year and positive liquid portfolio.
- Guardrail computations take about 20–45 seconds.
- Default local mode has no accounts.
- Not a licensed financial, investment, tax, or legal advisor.
Who it suits
driftcurve suits households exploring retirement or financial-independence scenarios and comfortable setting up a self-hosted tool. It may be useful to people who want to model varied household assets, debts, and spending assumptions.
Verdict
driftcurve offers detailed household inputs, return assumptions, and spending guardrails for retirement modeling. It is a modeling and educational tool, not professional financial, tax, or legal advice.
Plans and prices
From driftcurve's own pricing page, checked 15 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Free | Free | self-hosted · no subscription · no account in local mode |
The facts
Each one read from driftcurve's own pages, with the date it was checked.
What it does
- Account coverage
- Inputs include traditional, Roth, taxable, cash, real-estate and cryptocurrency assets.checked 15 Oct 2026
- Apache permissions
- Apache 2.0 grants perpetual, worldwide, royalty-free rights to reproduce, modify, display, perform, sublicense and distribute the work subject to its conditions.checked 15 Oct 2026
- API
- The documented API includes forecast and guardrails endpoints, plus authentication, profile, and scenario endpoints for multi-user mode.checked 7 Oct 2026
- Authentication security
- The multi-user implementation hashes passwords with PBKDF2-SHA256 and uses server-side session cookies.checked 15 Oct 2026
- Calculation limit
- Guardrails require a retirement year and positive liquid portfolio, and the README says a computation takes about 20–45 seconds.checked 7 Oct 2026
- Debt and income inputs
- The scenario model includes mortgages, HELOCs, student loans, pensions, Social Security and property sales.checked 15 Oct 2026
- Dependencies
- The project declares FastAPI, Uvicorn, aiofiles and SQLAlchemy as runtime dependencies.checked 15 Oct 2026
- Developer API
- The repository documents /config, /forecast, /guardrails, authentication, profile and scenario endpoints.checked 15 Oct 2026
- Forecast caveat
- The maker says forecasts are projections based on historical data and user assumptions, not predictions, guarantees or professional financial advice.checked 15 Oct 2026
- Guardrail API
- POST /guardrails accepts the same scenario body as /forecast and returns spending, thresholds, achieved probabilities and configuration.checked 15 Oct 2026
- Guardrail defaults
- The documented defaults target 0.80 probability of success, with upper and lower trigger probabilities of 0.99 and 0.25.checked 15 Oct 2026
- Guardrail limitation
- Guardrail calculations require a retirement year and a positive liquid portfolio.checked 15 Oct 2026
- Guardrail speed
- The README estimates a guardrail computation at roughly 20–45 seconds.checked 15 Oct 2026
- Hosted mode
- An optional multi-user mode supports email/password accounts, server-side sessions, and profiles and scenarios stored in driftcurve.db.checked 7 Oct 2026
- Household modeling
- The model supports multiple people with separate retirement dates and savings rates.checked 15 Oct 2026
- Installation
- The quick start creates a Python virtual environment, installs requirements and runs Uvicorn on localhost:8000.checked 15 Oct 2026
- Intended use
- The README presents driftcurve for household retirement planning, including financial-independence planning scenarios.checked 7 Oct 2026
- Licence
- The project is released under the Apache License 2.0.checked 15 Oct 2026
- License
- The project is open source under the Apache License 2.0.checked 7 Oct 2026
- Limit: no guarantee
- The licence and README disclaim warranties and liability, and the maker warns that outputs can be materially wrong.checked 15 Oct 2026
- Limit: optimistic history
- The README characterizes the 1966–2024 period as still optimistic, with a median 90%-equity/10%-bond blended CAGR of about 10.2% annually.checked 15 Oct 2026
- Local privacy
- In default local mode, household information and saved scenarios remain in browser localStorage and are not written to a database.checked 15 Oct 2026
- Market series
- The historical simulation covers S&P 500, 10-year Treasuries, residential real estate, CPI and Bitcoin returns.checked 15 Oct 2026
- Method context: cash flows
- Kitces explains that Social Security, pensions, rental income, part-time work and property changes can materially alter portfolio withdrawals.checked 15 Oct 2026
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