Five minutes in. Real answers out.
fingine.ai runs a short conversational intake, builds a typed financial model, and answers your what-if questions against deterministic math. The AI picks the right tools; the server does the arithmetic. No LLM in the math path.
The flow
Sign in
Google sign-in. We never see your password. Magic-link is on the roadmap.
Pick a workspace
Business or Life. Two projects per account, kept separate on purpose. Decisions for the company go in Business; decisions for you go in Life.
Five-minute intake
Seven mandatory questions about your cash, revenue, headcount, opex, and fundraise plans. The agent walks you through one at a time. You can type numbers in your local format ("1.5 lakh", "50k", "2 cr"); the engine cross-checks the magnitude before storing.
Your runway lands
A single trustworthy number, with the math one click away. "Show the math" expands to: cash on hand, MRR, MoM growth, total monthly cost, average burn over the next 6 months, and the formula. Same inputs always give the same number.
Ask any "what if"
"What if we hire 2 engineers in June at $15k/mo each?" The agent calls the right named-mutation tool, the engine recomputes, and the runway moves. The reply names what changed and how the number moved — never invented, always reproducible.
Decisions, with follow-ups
For "should I / can I afford to" questions, the agent walks you to a recommendation: a decision card with the WHY, the runway impact, and an optional list of "things to come back on" later (watch MRR, re-evaluate hire ramp, cash buffer alert). You return weeks later to mark each "happened" or "didn't happen". That's the feedback loop.
Why this works
The math is deterministic. The runway calculator is pure-function TypeScript, server-side, with 100% test coverage. Same inputs always give the same number. The LLM never invents a runway figure.
Inputs are auditable. Every money tool call must include the user's plain-language form ("₹50 lakh", "$500k") alongside the integer minor units. The engine cross-checks them before storing — magnitude errors get rejected at the boundary.
Sources are curated. When the agent searches the web for founder context (norms, regulations, market data), it pulls from a hand-picked allowlist of about 100 trusted sources. No Twitter. No Reddit. No generic Medium.
Trust is the binding constraint. One wrong runway number kills the product in this segment. Every output traces to an input you gave. If a number is wrong, you can find the input that's off and fix it.
Try it →