Baynota turns prior financial records into a live DCF engine that eliminates long manual setup. Historical statements become forecast structure, assumptions become machine-assisted, and valuation outputs arrive faster with cleaner logic.
Historical records become modelling input, not dead archives.
Unlevered FCF — FY23A to FY28E
Sensitivity Matrix — WACC × Exit Multiple
Implied Share PriceSetup time
Minutes
Scenarios
Multi-case
From records to first-pass model
What used to take long hours of spreadsheet construction becomes an automated starting point with cleaner logic and better continuity across periods.
Scenarios generated automatically
The platform builds multiple valuation cases at once, so teams stop wasting time duplicating tabs and reworking formulas for every new assumption set.
Assumptions grounded in history
Forecast logic is not invented from scratch every time. It is anchored in prior records, making outputs easier to defend internally and externally.
The engine pulls prior financials, normalises line items, and reconstructs trend logic across revenue, margin, capex, working capital, and cash flow drivers — automatically.
What gets removed
Tedious work the engine takes off the table.
Historical line-item cleanup
Forecast tab scaffolding
Formula linking across statements
Sensitivity table rebuilding
Scenario duplication and QA
Manual valuation bridge formatting
Typical output stack
“Historical records become modelling input, not dead archives.”
4-step
Automated pipeline
Multi-case
Scenario generation
Traceable
Assumption grounding