Due diligence · Startup diligence
AI startup due diligence that structures the work on private deals
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Thesis, bull and bear case, key metrics, comparables and risk flags, synthesized into one structured tear-sheet.
Thesis
Bull case
Bear case
This name is not publicly listed, so there is no market data to show. The card covers the thesis, both sides of the argument and the risk flags.
Key metrics
Comparables
Risk flags
Market data from public sources, as of . Informational only, not financial advice. Qualitative card, no public market data for this name. Informational only, not financial advice.
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Diligence on a startup is messier than on a public company. There are no audited filings, the data is whatever the founder shares, and the real questions, market size, team, traction, defensibility, are easy to skim past in the excitement of a deal.
Investables.ai brings structure to AI startup due diligence on private companies that are publicly known. Enter the company name and the card sets out the thesis, the bull and bear case, comparable public companies and the risks, written from public information about the business. It does not read decks or data rooms, so pair the card with the documents the founder shares. It keeps angels and venture investors consistent across a busy pipeline. It is informational research to support your own diligence, not investment advice.
Both sides bull and bear
Risk flags on every card
The short answer
What does startup due diligence cover?
Six areas: the market and its real size, the team and their track record, traction evidence such as revenue quality and retention, the business model and unit economics, defensibility, and the legal and cap table position. Because there are no audited filings, the work is mostly about testing which founder claims are verifiable. For a publicly known private company, Investables.ai gives you a first pass on the market, the comparables and the risks, so you know which founder claims to test first.
Why it works
What structured startup diligence actually looks at
Structure before the pitch
Market, model, comparables and risk are organized into a consistent frame, so you start each deal from the same structured view.
Hard questions surfaced
The open questions and risks a founder will not volunteer are listed plainly, so you walk into the conversation prepared.
Pipeline-wide rigor
Every deal runs through the same process, so the tenth pitch of the week gets the same scrutiny as the first.
What you get
Structure for a deal that has no audited filings
Market and competition, the business model, comparable public companies and a candid list of risks for a publicly known private company, written from public information rather than from a 10-K that does not exist.
- A first pass on publicly known private companies
- Market and competition in plain language
- Business model and comparable public companies
- The key risks to test with the founder
- Keeps your diligence consistent across deals
Thesis
Dominant AI accelerator supplier. The debate is the durability of data-center demand versus a cyclical capex peak.
Bull
CUDA moat, near-monopoly share
Bear
Customer concentration, cycle risk
Side by side
The six diligence areas and what evidence to demand
Startup diligence fails when a strong narrative substitutes for evidence. Each area has a claim founders make and a document that tests it.
| Area | The claim to test | Evidence that settles it |
|---|---|---|
| Market | The addressable market is large | Bottom-up sizing from real customer counts and price points, not a top-down analyst chart |
| Team | This team can execute | Prior operating history, domain depth, how long the founders have worked together |
| Traction | Growth is accelerating | Cohort retention, revenue quality, share of revenue from the largest customer |
| Business model | Unit economics work at scale | Gross margin per customer, payback period, contribution margin after support costs |
| Defensibility | Competitors cannot copy this | Switching costs, data or network effects, proprietary distribution |
| Legal and cap table | The structure is clean | Option pool size, prior round terms, liquidation preferences, IP assignment |
Informational research only. Investables.ai supports your diligence process and does not value private companies, recommend investments or replace legal or accounting review.
Why Investables.ai
The same questions on the deals you like and the ones you do not
Enthusiasm is the main failure mode in private diligence. Running every opportunity through an identical structure is what stops the exciting deal getting a lighter check than the boring one.
Both sides, every time
The bull case and the bear case sit side by side, so you weigh the argument instead of reading a single take. Informational only, never a recommendation.
Risks on the page
Valuation, concentration and regulatory risks are flagged explicitly, so the downside is visible up front rather than buried in a footnote.
Faster diligence
A structured first pass in seconds means you spend your time on judgement, not on gathering, across stocks, ETFs, crypto and startups.
Good questions
Questions about startup diligence
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Enter any ticker or asset and read the thesis, both sides of the argument and the risk flags in seconds. Built to make your own diligence faster. You decide, every time.
Informational only, not financial advice · past performance does not guarantee future results