Finicast

Open a demo model.

Each is a live workspace built from a tested document: change a driver, watch every statement follow, download the workbook. The document behind each one is linked, so an agent can start from it.

Three-statement forecast

Income statement, cash flow and balance sheet for CoreWeave, driven by an editable assumptions table. Built by Claude from one prompt.

Open a demo model for a company forecast → Document

DCF valuation

Unlevered free cash flow with mid-year discounting, a WACC build-up, perpetuity and exit-multiple terminal values, the equity bridge, and sensitivity tables of price per share.

Open a demo model for a DCF → Document

Comparable companies

Apple against seven peers: EV/Revenue, EV/EBITDA, P/E, growth and margins on LTM and NTM, peer statistics, and the implied price. Edit any input.

Open a demo model for comps → Document

Precedent transactions

Twelve software deals with terms and premiums, statistics over the set and its subsets, and the implied value of the target at each.

Open a demo model for precedents → Document

Sales operations

A $55M ARR SaaS sales org: 2,000 opportunities, funnel, BDR scorecards, quotas, accelerators, kickers and SPIFFs, with dashboards for the CRO, VP Sales, sales ops, reps, SDRs and marketing.

Open a demo model for sales ops → Document

Budget vs actual

A ledger rolled into subsidiary × department × line × month, budget and variance as versions, manager commentary alongside.

Open a demo model for FP&A → Document

Ledger to model

A general ledger CSV becomes a monthly operating plan: actuals through August, a driver-based forecast, budget beside outlook, YTD and full-year by entity and department.

Open a demo model for a ledger → Document

Scenario analysis

Bear, base and bull as a dimension: one rule set, drivers per case, results side by side.

Open a demo model for scenarios → Document

From prompt to model in three steps.

The agent writes rules, not cells.

revenue[frame=fcst] = PREV(revenue) * (1 + growth)
gross_profit        = revenue - cogs
cash[frame=fcst]    = PREV(cash) + cash_flow.free_cash_flow

Finicast calculates every period.

Income statement, cash flow, balance sheet. One document in, statements and a link out.

You steer.

Change a driver. Every dependent cell updates in milliseconds, for everyone with the link.

Operating model · line × period · 8 rules

The Finicast workspace: line items on rows, years on columns, the rule bar below

Built for agents. Made for people.

Rules, not cells

A rule names a line item and the region it covers. One rule, every forecast period.

A real dependency graph

An edit recomputes only what depends on it. Verified against a reference evaluator.

Dashboards people can edit

Drivers in a table, KPIs and charts that follow. The agent declares them in the same document.

Every interface an agent needs

MCP, REST, a JSON model document, an npm CLI, a skill file. Every error carries a fix.

Why not a spreadsheet, or a script.

	Spreadsheet	Script	Finicast
A 40-line, 12-period statement	480 cell formulas	A few hundred lines	≈ 12 rules
Forecast vs. actual periods	Hand-picked ranges	Index arithmetic	frame = fcst
One input changes	Whole workbook	Re-run the script	Only what depends on it
What the person gets	A file	A number	A live model to steer

One document in. Statements and a link out.

{
  "periods":  { "start": "2022-01", "count": 9, "grain": "year", "histUntil": "2025-12-31" },
  "pivots": {
    "assumptions":      { "lines": ["revenue_growth", "gross_margin"], "inputs": { "revenue_growth": { "fy2026": 0.6 } } },
    "income_statement": { "lines": ["revenue", "cogs", "gross_profit"],
                          "inputs": { "revenue": { "fy2025": 5131 } },
                          "rules":  "revenue[frame=fcst] = PREV(revenue) * (1 + assumptions.revenue_growth)" }
  },
  "outputs": "all",
  "dashboards": "auto"
}

curl -X POST https://finicast.com/api/build --data @model.json
# → statements as markdown + a link to the live workspace

Hosted MCP finicast.com/api/mcp
Local npx -y finidb mcp · build offline with finidb build
Source-available under PolyForm Noncommercial

Docs for agents → llms.txt

Financial models, built by your AI agent.