Your personal financial advisor

Create Plaid app credentials, implement Link flow, exchange public token, store access tokens securely.

Implement initial and recurring sync for accounts, balances, transactions, and (where supported) investment holdings.

Design database schema for users, institutions, accounts, transactions, categories, holdings; normalize incoming data.

Handle disconnected accounts, multi-factor prompts, token expiration, and user re-link flows.

Encrypt sensitive data at rest, secure secrets, set least-privilege access patterns.

Implement Google and Apple OAuth sign-in; handle account creation, sessions, and logout.

Store basic user profile, timezone, currency, and notification preferences.

Ensure all financial data is scoped to the authenticated user; implement authorization checks across APIs.

Define scenario inputs, assumptions, and outputs; build a modular simulation framework to support multiple scenario types.

Model contributions, expected returns, inflation assumptions, withdrawal rate, and target dates; show projection charts and milestones.

Run Monte Carlo simulations for portfolio outcomes using configurable return/volatility assumptions; present probability bands and risk metrics.

Model down payment, mortgage terms, rate, taxes/insurance/maintenance assumptions, and impact on cashflow and net worth.

Recommend relevant scenarios and pre-fill reasonable defaults based on observed cashflow, portfolio, and goals; allow user to override inputs.

Build UI to run simulations, view results, and save/compare scenarios over time.

Compute month boundaries and aggregate net worth, cashflow, spending categories, and portfolio summary metrics.

Build a monthly report view with key metrics, charts, and breakdown tables (web).

Implement holdings/asset allocation summary and basic performance calculations based on available data.

Income vs spend, category breakdown, top merchants, unusual spend flags (simple heuristics).

Optional PDF export and/or email delivery; confirm scope for MVP.

Build a chat interface with conversation history, citations to underlying data where possible, and clear disclaimers.

Generate proactive insights (e.g., unusual spend, cash drag, concentration risk, savings rate) using heuristics plus AI summarization.

Assemble user financial context (net worth, cashflow, holdings) and ensure data access is scoped per user.

Collect basic user goals (e.g., retire by X, buy house, risk tolerance) to tailor advice and simulations.

Add guardrails, explain limitations, avoid regulated advice claims; include disclaimers and escalation to 'talk to a professional' messaging.