Not a single forecast — three competing career-and-life strategies, each projected to the same goal year with the same engine. Every path is scored on endgame wealth, on-track probability, and cross-border readiness, then ranked side by side.

Each scenario carries its own compensation trajectory, equity grants, relocation timing, and tax exposure. The engine runs identical math across all three so the comparison is apples-to-apples — the only variables are the life choices.

Every plan runs 5,000 simulations with antithetic variates and a seeded PRNG — reproducible results, not random noise. The headline is a probability (the odds of clearing the goal) with a P10/P50/P90 cone, not a single tidy line pretending the future is certain.

Antithetic variates pair each random draw with its mirror, cutting variance in half for the same number of runs. The seeded generator means you get the same result on every page load — until you change an assumption.

Every input is modeled worst-case to best-case — conservative and aggressive returns, base and stretch career arcs, weak and strong rupee. You see the honest downside and the full upside, never just the rosy midpoint.

Uncertain upside (like rental income on a property you haven't bought) goes into the ceiling only, never the floor. The floor is what you can count on; the ceiling is what's possible if things break your way.

Drag any assumption — equity return, FX drift, inflation, savings rate — and the full projection recomputes instantly in your browser. No server round-trip, no loading spinner. The model isn't a black box; it's a thing you can poke.

The engine is deterministic and client-side: the same inputs always produce the same outputs. Changing one lever reruns the entire Monte Carlo + scenario stack in milliseconds, so you feel the tradeoff immediately.

Checking, savings, credit cards, and retirement accounts sync via Plaid. Net worth updates every time you open the app — no manual entry, no stale spreadsheet.

Your self-directed brokerage is itemized holding by holding, each repriced from live market quotes. Unrealized gain/loss, today's move, and the full position table — mirroring your broker, but wired into the projection engine.

RSU grants are tracked grant by grant with their real vesting schedule, repriced at today's share price. Vested shares feed the brokerage; unvested shares feed the scenario projections. A pending offer is modeled as "projected" on a back-loaded 5/15/40/40 vest, with a dashed border and a badge — it never masquerades as settled wealth.

Each vest date, share count, and grant origin is explicit. The engine prices unvested shares at today's stock price and projects them forward as part of the career scenario, so the 10-year trajectory includes equity you haven't received yet.

Your US home value comes from RentCast (Zillow-grade AVM), and the engine calculates amortized mortgage payoff, closing costs, and net proceeds — timed to your planned move year. The sale proceeds flow into the cross-border projection automatically.

The USD/INR rate and gold spot price are pulled live, not hardcoded. Your Indian assets and gold holdings are valued at today's rate, and rupee depreciation is baked into the long-term projection — not as a guess, but as a modeled drift with a range.

Year-over-year trend attribution, category spike detection, clear-win identification, savings-rate analysis, and median-burn context — all generated from coded statistics over your SpendingDigest, not AI tokens. The insights are instant, deterministic, and free.

The engine computes YoY deltas per category, identifies the biggest movers (up and down), calculates your trailing-12-month median burn, and generates templated prose from the numbers. Claude is available as a fallback if you explicitly request it, but the default insights cost zero tokens.

Every merchant is categorized using 80+ pattern-matching rules across 18 categories — from Indian jewelers (Gold) to childcare providers to credit-card payments (Internal). Plaid's raw category constants are mapped to clean labels as a fallback. No AI call needed for the vast majority of merchants.

The pattern engine covers groceries, dining, transport, travel, housing, utilities, health, subscriptions, investments, gold, India support, and more. When a merchant doesn't match any pattern, the Plaid category maps to the closest clean label. AI categorization is still available as an explicit fallback for edge cases.

Large transactions still classified as spending get a second-pass review using pattern matching — transfer language, refund signals, investment keywords, and deposit indicators flag likely misclassifications. Each proposal shows the suggested bucket and a one-line reason.

The deterministic pass catches own-account transfers, loan payments, brokerage moves, refunds, and insurance payouts that survived the first classification. AI review is available as a fallback for ambiguous transactions the rules can't confidently reclassify.

Every transaction lands in one of ten buckets — five mandatory (housing, food, transport, health, debt), five discretionary (personal, travel, shopping, entertainment, subscriptions). Each bucket is labeled cuttable or non-negotiable, so the runway calculator knows exactly where the slack is.

The taxonomy is designed for a specific purpose: answering "how long can I survive if I cut everything optional?" The engine uses the mandatory/discretionary split to stress-test your runway under different austerity scenarios.

Ask anything about your finances in plain English. The engine interprets the question, pulls the relevant data, and answers with numbers and context — no menu-diving, no query syntax. In the demo, visitors can bring their own API key to unlock live AI answers.

Most apps project runway from a budget you set. This engine uses your real trailing 12-month spending — after excluding one-time outliers — to calculate how many months of cash you have. The number is honest because the input is real.

The engine separates one-time spikes (a car down payment, a medical bill) from your steady-state burn rate. Runway is based on the steady state, so a single large purchase doesn't panic the model.

Three tiers of stress: current burn rate, belt-tightened (mandatory-only spending from the 10-bucket split), and worst-case (job loss + mandatory only). Each scenario shows months of runway and the cash-out date, so you know exactly how much margin you have.

Compensation assumptions aren't guesses — they're sourced from Glassdoor, Levels.fyi, and industry surveys, with the source cited next to every number. When the engine says "Senior Product Designer at Google in Hyderabad: ₹95–99L," that's a researched range, not a vibes estimate.

US dollar and Indian rupee assets are tracked natively — bank accounts, real estate, gold — each in its local currency, converted at the live FX rate for the combined view. No manual currency juggling.

The projection doesn't assume a fixed exchange rate. It models rupee depreciation as a range (floor and ceiling drift), so your ₹-denominated goal is stress-tested against currency headwinds. Indian assets that are priced in rupees are immune to this depreciation — the engine knows the difference.

The US home sale is modeled with a live valuation, amortized payoff schedule, and closing costs — timed to the year you plan to relocate. The net proceeds inject into the projection at exactly the right point in the timeline.

The ₹70 Cr target includes ₹ trusts for each child, carved out as a separate line in the goal breakdown. The engine tracks "after trusts" wealth separately, so you always know what's yours versus what's earmarked.

All computation — projections, Monte Carlo, scenario scoring — runs locally on your device. There is no cloud backend storing your financial data. The app reads your data files and computes everything in-process.

Plaid connects to your banks with your explicit authorization, and the credentials live with Plaid's infrastructure (never in the app). You can disconnect any account at any time, and the app continues to work with cached data.

The default path for insights, categorization, and anomaly detection uses zero AI tokens — pure statistics and pattern matching. AI is only called when you bring your own API key. When it is called, it sends the minimum context needed and discards your key after the request. No financial data is stored by the AI provider, and no model is trained on your numbers.

Paste your Anthropic API key to unlock Claude-powered features across the entire app — AI spending insights, intelligent merchant categorization, anomaly detection, and natural language questions. The key stays in your browser's localStorage and is sent per-request, never stored server-side.

Without a key, every feature still works — the engine falls back to statistical insights, rule-based categorization (80+ patterns), and pattern-matched anomaly detection. The key is a toggle: enter it and everything upgrades to AI; remove it and everything reverts to the free, instant defaults.

The projection engine is pure math — given the same inputs, it produces the same outputs, every time. No opaque ML model deciding your future. Every assumption is visible, every number is traceable, and the methodology is documented right here.