Run a valuation
Every step the agent runs to build a discounted-cash-flow valuation.
This page documents the retired standalone DCF pipeline, kept so reports that ran on it still link here. New analyses run the adaptive pipeline, which picks the valuation shape — including this DCF — from the company's facts.
A DCF analysis ran a series of AI agents. Some ran side by side, some ran in a loop. Together they researched the company, built a discounted cash flow valuation in Damodaran's framework, pressure-tested it, and wrote the report. Click any node in the graph to jump to that step here.
The pipeline moves through four phases. Research gathers the facts, Valuation turns the story into numbers, Analysis challenges those numbers, and Assembly builds what you download.
dbot pulls recent news in a few buckets: the company itself, earnings, strategy moves like launches and acquisitions, what competitors are doing, and where the industry is heading. It also runs searches aimed straight at your thesis, looking for anything that backs it up or argues against it. Then it sorts what it finds by date and source and keeps facts separate from speculation.
dbot reads the company's latest 10-K, 10-Q, and 8-K filings and answers each of your framing questions with evidence pulled straight from the disclosures: the risk factors, the MD&A, the financial statements, and management's guidance. Every finding is cited by filing, date, and section.
For each framing question, dbot looks for evidence on both sides. It goes after the bear case and the competitive threats instead of just confirming the bullish view, and it weighs how good, how recent, and how reliable each piece of evidence is.
dbot pulls the three research streams (news, filings, and thesis evidence) into one brief. You get an executive summary, a read on the competitive landscape, an answer to each framing question, what it all means for the valuation, and a list of what's still unknown.
dbot sets Damodaran's valuation inputs, around twenty of them, and discounts the resulting free cash flows back to today. It makes sure the terminal return on capital clears the cost of capital and that reinvestment lines up with the growth rate you're assuming.
| Revenue growth | The near-term growth rate and how it tapers off over the forecast. |
|---|---|
| Operating margin | The margin the company settles at, and how long it takes to get there. |
| Sales-to-capital | How much revenue each dollar of reinvestment generates. |
| Terminal growth | Long-run growth, capped near the risk-free rate, usually about 2 to 3%. |
| Cost of capital | The discount rate (WACC) used to bring future cash flows to today. |
dbot runs the DCF in reverse. It nudges revenue growth, the target margin, or terminal growth to close the gap between its own fair value and the current price. Each pass changes the one input that matters most, and it stops once the estimate lands within tolerance or it hits the iteration cap. Then it tells you what the market price is really assuming.
dbot runs ten scenarios, changing one key driver at a time (revenue growth, operating margin, terminal growth). It works through how each change moves the value, then gives you a fair-value range and ranks the drivers by how much they matter.
dbot pulls the sell-side consensus: price targets (low, average, high), EPS and revenue estimates, and the mix of buy, hold, and sell ratings. It lines those up against its own fair value and growth assumptions and explains anywhere the two really disagree.
dbot grabs data on the peer group and works out the usual multiples (P/E, P/S, EV/EBITDA). It checks the company's DCF-implied multiples against its peers to see whether a premium or discount actually makes sense given the fundamentals.
This is a Professor-Damodaran-style review of the base DCF, and it ends with a clear approve or reject.
dbot pulls everything together (the research, the DCF, the convergence work, the sensitivity range, the consensus comparison, the comparables, and the critic's verdict) into a tight six-paragraph brief: what the research found, what the valuation says, the assumptions it leans on, how the pieces fit, where it lands against Damodaran's principles, and the risks worth watching.
dbot makes four valuation charts (a valuation bridge, the cash-flow projection, the peer comparison, and a sensitivity heatmap) plus the Damodaran-style tables: the DCF one-pager, story-to-numbers, your estimates versus the market, and the financial foundations.
dbot fills in a Ginzu-style DCF spreadsheet with the final inputs (growth rates, margins, sales-to-capital, terminal growth, and the cost of capital) so you can download the model and push on the assumptions yourself.
dbot writes the long-form, Damodaran-style report. It takes your thesis and framing questions head-on, drops in the charts, links the Excel model, and includes the DCF and comparables tables and the sensitivity table. It runs from an opening market observation to the valuation thesis, then a walk through the numbers, the counter-arguments, and a balanced close. No buy or sell calls, and it ends with three things to watch.
When the pipeline finishes, head to Viewing a report to read it, or Downloading PDF, Excel & charts to grab the files.