// THE LEXICON OF CAPITAL
The Lexicon of Capital
In category creation, he who defines the terms owns the market. Here are the official definitions for AI Judgment Infrastructure™ and the terminology that compiles systematic capital allocation.
New here? Start with What is askOdin?
- AI Judgment Infrastructure™
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A technological framework designed to systematize high-stakes capital allocation decisions. Unlike Information Infrastructure (which retrieves and organizes data), Judgment Infrastructure interrogates the logical coherence of an investment thesis.
// CONTEXT
Used by Institutional VCs and Private Equity to audit deal flow, identifying structural risks before capital is committed.
Keywords: Capital Allocation, Due Diligence, Systematized Judgment.
- Brittle Assumption
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A foundational premise in a business model that, if proven false, causes the entire venture to collapse. Unlike a standard "Risk" (which can be mitigated), a Brittle Assumption is binary: it holds, or the company dies.
// EXAMPLE
"We assume consumers will change 20 years of behavior to save $2."
Critical for capital allocators to identify before committing investment.
Applied: private-market risk scoring, the Audit Gap.
- The Clarity Score™
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A standardized deterministic score (0–100) indicating the structural integrity of a startup narrative for capital allocation purposes. It is calculated by weighting four vectors:
- • Logical Consistency — Mathematical coherence between claims
- • Evidence Provenance — Audit trail of data sources
- • Semantic Stability — Language precision vs. vague positioning
- • Unit Economic Physics — Compliance with economic gravity
// NOTE
It is not a prediction of success, but a measure of investability.
Applied: how a Clarity Score compiles, risk scoring in practice.
- The Judgment Graph™
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A proprietary vector database connecting 100,000+ Clarity Scores calibrated on public deal data. It maps semantic patterns in pitch decks to historical commercial outcomes (IPO, Bankruptcy, Acquisition), allowing the engine to "pattern-match" strategy against the "Universal Grammar of Failure."
Unlike generic LLMs trained on "everything," the Judgment Graph is outcome-labeled: every pattern is connected to a known result. This enables deterministic capital allocation risk assessment rather than probabilistic guessing.
Applied: the Provenance Ledger.
- Logical Consistency (Vector I)
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The mathematical coherence between a startup's claims in their investment thesis.
// TEST
Does the Customer Acquisition Cost (CAC) defined on Slide 8 mathematically support the Runway projections on Slide 12? If the math conflicts, the narrative is incoherent for capital allocation.
- Narrative Provenance (Vector II)
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The audit trail of data sources in an investment thesis. It distinguishes between:
- • Verified Data — First-party metrics with source documentation
- • Inferred Estimates — Market sizing, TAM projections
- • Ungrounded Claims — Unsupported assertions masquerading as facts
Critical for venture capital due diligence.
Applied: the Provenance Ledger, the Defensible Audit Log per deal.
- Semantic Stability (Vector III)
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A measure of language precision in startup narratives for capital allocation evaluation.
- ✓ High Stability: Specific, falsifiable claims (e.g., "30% MoM growth")
- ✗ Low Stability: Vague positioning (e.g., "Huge opportunity," "Disruptive tech")
Used to filter signal from noise in venture investment evaluation.
Applied: drift across CIM, model and disclosures.
- Regulatory Physics (Vector IV)
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The compliance with market laws and economic gravity in venture theses. Checks against:
- • Insurmountable regulatory barriers (e.g., FDA phases, banking licenses)
- • Unit economic impossibilities (e.g., negative gross margins at scale)
Essential for private equity and venture capital risk assessment.
Applied: PE and M&A data-room diligence.
- The Judgment Gap
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The failure to apply rigorous interrogation to investment theses despite having abundant information. This is the core problem causing systematic failures in capital allocation.
The Judgment Gap explains why sophisticated teams with comprehensive data still make systematically flawed venture decisions. They have access to every metric and comparable, yet consistently miss critical risks that experienced partners identify intuitively.
Discovered by askOdin's founder through analysis of hundreds of deals on both sides of the allocation table at SilkRoute and Awesome Ventures.
Applied: the Audit Gap in venture capital.
- The Clarity Framework™
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askOdin's proprietary, end-to-end system that compiles the public Clarity Protocol into institutional-grade, defensible judgment for capital allocators.
The complete infrastructure for systematically evaluating venture investment theses. It includes:
- 1. The "Scar Tissue to Data Asset" Process
- 2. The Judgment Engine & Analytics
- 3. The Human-AI Collaboration Layer
Applied: the compile methodology.
- Strategic Incoherence
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A fatal state where a founder pursues mutually exclusive go-to-market strategies simultaneously (e.g., trying to be a high-touch Enterprise B2B platform and a low-cost B2C app at the Seed stage).
This is the most common reason early-stage ventures fail to gain traction despite strong product-market fit signals. A critical filter for capital allocators.
Applied: pitch-deck structural analysis.
- Innovation Theater
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Non-binding partnerships, LOIs (Letters of Intent) with no commercial value, or pilot programs designed to make a corporate partner look innovative without resulting in recurring revenue.
The Crucible™ flags these aggressively during venture capital due diligence, as they are often presented as "traction" but have zero predictive value for actual growth or capital deployment success.
Applied: VC due diligence.
- The Clarity Protocol
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The public blueprint of six essential questions for investment rigor that form the foundation of askOdin's judgment methodology for capital allocation.
These questions represent the minimum viable interrogation framework every capital allocator should apply to high-stakes decisions. The Protocol is open and freely available — it's the "recipe" for rigorous analysis.
The Clarity Framework™ is how askOdin systematically executes this protocol at institutional scale for venture and private equity.
Applied: the methodology, the founder pitch test.
- 4-Dimensional Risk Audit
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askOdin's systematic interrogation framework that stress-tests investment theses across four critical domains:
- • Market: Is the addressable market real, accessible, and economically viable for capital allocation?
- • Model: Do the unit economics scale positively under realistic investment assumptions?
- • Moat: Is the competitive advantage defensible against well-funded venture-backed incumbents?
- • Management: Does the team have domain-specific scar tissue and execution capability?
This framework is hardcoded into The Crucible™ and Clarity engines to ensure every venture thesis receives comprehensive structural interrogation.
Applied: AI due-diligence software, run one in the sandbox.
- Kill Shot
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A terminal flaw detected by the RUNE Protocol — a structural contradiction so fundamental that no amount of narrative polish can fix it. When a Kill Shot is detected, the Clarity Score collapses to zero.
// EXAMPLES
Claiming revenue that contradicts financial model data. Assuming a TAM that physically cannot exist. Presenting regulatory approval as complete when it requires 5+ years of clinical trials.
Kill Shots are not "risks" — they are binary structural failures. Critical for capital allocators to identify before committing investment.
- RUNE Protocol™ U.S. PATENT PENDING 63/948,559
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askOdin's patent-pending judgment compiler (U.S. Provisional Patent No. 63/948,559). The RUNE Protocol compiles unstructured deal flow — pitch decks, data rooms, financial models — into computable syntax for risk assessment in capital allocation.
Unlike information-layer AI that summarizes or generates text, the RUNE Protocol operates at the judgment layer: it tests whether the logical claims in a venture thesis can physically coexist. It is the rails upon which both The Crucible and Clarity run.
// ANALOGY
If Visa verifies whether a financial transaction can clear, RUNE verifies whether an investment thesis can clear.
Applied: how RUNE compiles a deal room.
- Dual Score Protocol
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Clarity's two-layer scoring system for capital allocation triage at institutional scale.
- • Layer 1 — Clarity Score (0–100): Rates narrative integrity across Story Quality, Market Evidence, Unit Economics, and Team Signal.
- • Layer 2 — Severity Taxonomy: Classifies every finding as Critical, Major, or Minor — enabling fast triage of large venture pipelines.
Together, these layers let partners focus on the 2–3 deals with valid physics and skip the 500 with narrative masking. Used in Clarity's Pipeline Dashboard for institutional deal flow management.
Applied: the founder pitch test, pipeline triage scoring.
- Semantic Sycophancy
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The foundational computational flaw inherent to all large language models: the neural network is mathematically weighted to prioritize confident, fluent narrative tokens over mathematical truth — appeasing the reader rather than auditing the claim. It is the LLM vulnerability askOdin was built to cure, and the underlying cause of Narrative Masking.
// THE ASKODIN RESOLUTION
LLMs optimize for persuasion. askOdin compiles for physics. We restrict the LLM to a non-generative extraction role, then compile the extracted variables through a deterministic engine — so the model's sycophancy never reaches the final Verdict.
Related: Narrative Masking (the operational symptom this flaw triggers).
- Semantic Drift
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Divergence between narrative presentation and structural integrity measured across chronologically sequential documents — the same company at T₀ and T₁. When presentation inflates while the underlying structural variables degrade, the NORN Protocol™ raises a compile-time error.
This is the temporal case. Its intra-document counterpart, caught inside a single model response, is Narrative Masking. Two protocols, two filings, two different boundaries: NORN reads a company against its own history, JUDGE reads a response against itself.
// WHY IT MATTERS
A deck that reads better each round while the financials read worse is the single most common signature preceding a down round. It is invisible in any one document and obvious across three.
Applied: drift across CIM, model and disclosures, the NORN Protocol.
- Narrative Masking
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The operational threshold the JUDGE Protocol™ triggers when Semantic Sycophancy manifests inside a single model response — when the narrative density of that response diverges from the structural variables it actually extracted. It actively conceals brittle assumptions by generating false comfort.
It is an intra-document state, caught at runtime before a result is written. Measure the same divergence across chronologically sequential documents and you are looking at Semantic Drift instead — a different protocol, a different patent.
// THE ASKODIN RESOLUTION
LLMs optimize for persuasion. askOdin compiles for physics. We restrict the LLM to a non-generative extraction role, then compile the extracted variables through the deterministic JUDGE Protocol™ to enforce structural physics — preventing the masking from contaminating the final Verdict.
Related: Kill Shot, Narrative Masking in practice. Critical for capital allocators evaluating AI-generated venture analysis.
// THE DEAL DESK
The Deal Desk
The vocabulary of private-market diligence, read forensically. Every entry states what the term means, how it gets gamed in a live transaction, and how to test it before capital is committed. We did not name these terms. We re-read them.
- Add-Back PE
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An expense a seller removes from historical EBITDA on the grounds that it does not reflect the ongoing economics of the business — owner compensation above market, a one-time legal settlement, rent paid to a related party.
Purchase price is a multiple of adjusted EBITDA, so an add-back does not enter a deal at face value. It enters at the multiple. At 8x, a $500,000 add-back that fails post-close scrutiny is a $4 million equity mistake.
// HOW IT GETS GAMED
Every add-back is a claim about the future filed as a statement about the past. The seller asserts a cost which did occur will not recur — a forecast, formatted as history. The most abused category is "non-recurring," because recurrence is a judgment call rather than an accounting fact.
// HOW TO TEST IT
Three properties, all three at once: it traces to specific ledger entries rather than an advisor’s summary schedule; it stays non-recurring when you widen the window past the period the seller selected; and the counterfactual survives — remove the founder’s above-market salary and you must add back the cost of replacing what the founder did.
Applied: AI Quality of Earnings , PE due diligence . Full entry: Add-Back.
- Working Capital Peg (the target) PE
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The normalized level of net working capital a buyer expects to be delivered at close, usually set as an average of trailing monthly balances. Delivery above or below the peg adjusts the purchase price dollar-for-dollar.
The peg is the second-largest silent price adjustment in a lower-middle-market deal and the one least likely to be modelled by the deal team. Unlike EBITDA, it moves cash at close and it moves it without a multiple to make the error obvious.
// HOW IT GETS GAMED
The averaging window is the lever. A seasonal business averaged across the wrong twelve months produces a peg materially below the level the business actually needs to operate — so the buyer funds the shortfall in cash after close, and calls it working capital rather than price.
// HOW TO TEST IT
Rebuild the peg on your own window, not the one in the draft agreement, and test it against the seasonal low point rather than the mean. Then check whether the peg reconciles to the same definition of working capital used in the model and the CIM — the three often quietly differ on cash, debt-like items and deferred revenue.
Applied: AI Quality of Earnings , PE due diligence . Full entry: Working Capital Peg.
- Quality of Earnings (QoE) PE
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An independent accounting analysis that tests whether reported earnings reflect sustainable, recurring operating performance — typically commissioned under exclusivity and delivered in three to six weeks.
The QoE is the instrument that validates the price. But it is commissioned after a price has been indicated, which means the deal team commits before the instrument finishes running.
// HOW IT GETS GAMED
Not gamed by sellers so much as mispriced by the market. At a five- to six-figure engagement cost, a QoE cannot be deployed on every top-of-funnel look — so the deals that most need scrutiny, the small ones, receive the least. The industry treats verification as a late-stage audit rather than top-of-funnel infrastructure.
// HOW TO TEST IT
Separate the two jobs. Screening — does the bridge reconcile, do the add-backs trace, does the same EBITDA appear in all four documents — is cheap and belongs before the LOI. Attestation-grade QoE is a different product and stays where it is. Confusing the two is what makes the sequencing fail.
Applied: AI Quality of Earnings , The methodology . Full entry: Quality of Earnings.
- EBITDA Bridge PE
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The schedule that walks reported EBITDA to adjusted EBITDA, line by line, showing every add-back and adjustment the seller has applied.
The bridge is where the deal is actually priced. Everything downstream — the multiple, the debt quantum, the equity cheque — is computed off the number at the bottom of it.
// HOW IT GETS GAMED
The bridge presents arguments in the visual grammar of arithmetic. A clean schedule in a familiar format reads as settled fact, when every line is a contested assertion. Length also works as cover: an eleven-line bridge is rarely challenged line by line under a deadline.
// HOW TO TEST IT
Read it as an argument, not a calculation. Assign each line one of three verdicts — traceable, unsupported, or contested — before you discuss the total. Anything not traceable to the ledger belongs on a challenge list before exclusivity, not in a QoE draft with three weeks left on the clock.
Applied: CIM analysis , The Provenance Ledger .
- Customer Concentration PE
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The share of revenue attributable to the largest customers, usually disclosed as a top-five or top-ten percentage of total revenue.
Concentration is the single most common reason an add-on acquisition underperforms its model. It is also the risk most easily flattened into a reassuring percentage.
// HOW IT GETS GAMED
Measured on revenue rather than gross profit, so a large low-margin account looks like diversification. Measured at the legal-entity level, so three subsidiaries of one parent count as three customers. And measured without contract term, so a top account on a 30-day rolling agreement reads identically to one with four years left.
// HOW TO TEST IT
Recompute on gross profit, roll subsidiaries up to ultimate parent, and overlay remaining contract term. Then check churn among the customers who were top-five three years ago — the historical churn rate of large accounts predicts more than the current concentration percentage does.
Applied: PE due diligence , Risk scoring .
- Run-Rate Revenue PE
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Revenue from a partial period annualized to represent a full year — most often a recent strong month or quarter multiplied out.
Run-rate converts a moment into a year. Where it feeds adjusted EBITDA, it feeds the multiple, and a single favourable quarter can carry a material share of the purchase price.
// HOW IT GETS GAMED
Period selection is the lever and it is almost never examined. The seller chooses which months to annualize; a business with any seasonality, any large one-off order, or any recently signed contract can produce a run-rate that the trailing twelve months does not support.
// HOW TO TEST IT
Annualize every available window, not the one presented, and plot them. If the seller’s chosen period is the outlier, the run-rate is a selection, not a measurement. Then check whether the costs required to sustain that revenue were annualized on the same basis — they frequently are not.
Applied: AI Quality of Earnings , CIM analysis .
- Earnout PE
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Deferred consideration contingent on the target hitting defined performance thresholds after close, used to bridge a gap between buyer and seller valuations.
An earnout does not resolve a disagreement about value. It defers it, and it defers it into a period when the buyer controls the business and the seller controls the grievance.
// HOW IT GETS GAMED
The dispute lives in the definitions, not the thresholds. If the earnout is measured on EBITDA, whose definition governs — before or after the buyer’s allocated overhead, integration cost, new hires, changed accounting policy? Ambiguity that reads as immaterial at signing becomes the entire argument at measurement.
// HOW TO TEST IT
Write the measurement calculation as a worked example, with real numbers, and have both sides sign it as an exhibit. Then run three scenarios: base, aggressive integration, and a downturn. If any produces a defensible reading in which both parties believe they are owed, the definition is not finished.
Applied: PE due diligence , The Provenance Ledger .
- Total Addressable Market (TAM) VC
-
The total revenue opportunity available to a product or service if it achieved complete market share — the ceiling a company’s growth narrative is measured against.
TAM sets the ambition of the story and therefore the valuation multiple the story can support. It is also the number least connected to anything in the financial statements.
// HOW IT GETS GAMED
Built top-down from an analyst report, then widened by redefining the category. The tell is a TAM whose implied unit economics contradict the company’s own reported pricing and cost structure — the market cannot be that large at the prices the company actually charges.
// HOW TO TEST IT
Rebuild bottom-up: units the company can realistically serve, times the price it actually achieves, times a defensible share. Then reconcile against the financials. Divergence between the narrative TAM and the numbers in the same document is the finding — we published the S-1 forensics on exactly this.
Applied: The WeWork S-1, audited , VC due diligence .
- Annual Recurring Revenue (ARR) VC
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The annualized value of a company’s recurring subscription contracts, presented as the headline measure of scale for subscription businesses.
ARR drives the revenue multiple. A definition that quietly stretches produces a valuation that stretches with it — and unlike EBITDA, there is no accounting standard governing what may be counted.
// HOW IT GETS GAMED
Committed, contracted and collected are three different numbers presented as one. Signed-but-not-started contracts, non-recurring services revenue, annualized pilots, and usage-based revenue extrapolated from a strong month all find their way into a single ARR figure.
// HOW TO TEST IT
Reconcile ARR to cash actually collected in the trailing twelve months and to recognized revenue in the financials. Then ask for the same figure split three ways: contracted and live, contracted and not yet started, and non-recurring. The gap between the headline and the first bucket is the real number.
Applied: VC due diligence , Pitch deck analyzer .
- Adjusted vs. Normalized EBITDA PE
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Adjusted EBITDA removes items a seller argues are non-recurring. Normalized EBITDA restates items to a market or steady-state level. They are different operations producing different numbers.
They are used interchangeably in CIMs, which lets one number carry both arguments without either being examined.
// HOW IT GETS GAMED
A cost is removed entirely as "adjusted" when the honest treatment is to restate it to market as "normalized" — the difference is the whole add-back.
// HOW TO TEST IT
For every line, ask whether the cost disappears or merely changes size. If it changes size, the bridge should show the replacement, not a removal.
Applied: AI Quality of Earnings .
- Pro-Forma Adjustment PE
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An adjustment reflecting cost savings or synergies identified but not yet realized, added to historical EBITDA as though they had been.
Pro-forma savings are not earnings. They are a plan.
// HOW IT GETS GAMED
The seller charges a multiple for the buyer’s own value-creation thesis, then the buyer books the same savings again in their model — the synergy is paid for twice and delivered once.
// HOW TO TEST IT
Strike every unrealized saving from the bridge and re-run the price. If the deal only works with them included, you are underwriting your own plan at the seller’s multiple.
Applied: PE due diligence .
- Exclusivity PE
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A negotiated period, typically 30 to 90 days, during which the seller agrees not to engage other buyers while the buyer completes confirmatory diligence.
Exclusivity looks like buyer protection. In practice the clock is a pricing lever, and it runs toward the seller.
// HOW IT GETS GAMED
A short window, granted late, ensures the buyer commits before verification completes. Every day spent discovering something that could have been screened pre-LOI is a day of leverage transferred.
// HOW TO TEST IT
Move everything cheap to verify before the LOI. Enter exclusivity to confirm a thesis, never to form one.
Applied: PE due diligence .
- Letter of Intent (LOI) PE
-
A largely non-binding document setting out headline price and structure, and triggering exclusivity ahead of confirmatory diligence.
The LOI is the moment leverage inverts. Before it you can walk cheaply; after it, walking has a cost and re-trading has a reputation.
// HOW IT GETS GAMED
Price is indicated off a CIM nobody has yet cross-examined, which makes every later correction look like a re-trade rather than a finding.
// HOW TO TEST IT
Treat the indicated multiple as conditional on the bridge reconciling, and say so in writing at indication rather than discovering it at week four.
Applied: CIM analysis .
- Indication of Interest (IOI) PE
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A preliminary, non-binding expression of interest with an indicative valuation range, submitted early in a sale process.
The IOI range anchors everything that follows, and it is set on the least verified information in the deal.
// HOW IT GETS GAMED
Bankers run processes to compress IOI timelines precisely so ranges are set on the CIM alone.
// HOW TO TEST IT
Screen the CIM against the financials before the IOI, not after. It is the cheapest verification in the entire process and the one with the most leverage attached.
Applied: CIM analysis .
- Confidential Information Memorandum (CIM) PE
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The sell-side marketing document describing the target’s business, market and financial performance, prepared by the seller’s advisor and issued to prospective buyers.
The CIM sets the frame for the entire process — including the adjusted EBITDA every subsequent number is measured against.
// HOW IT GETS GAMED
It is advocacy in financial formatting. Prepared by an advisor paid on outcome, it is structured to be persuasive and is routinely read as though it were disclosure.
// HOW TO TEST IT
Read it as a claim set. Every figure that materially affects price should reconcile to the financial model, the management presentation and the lender deck. Where four documents disagree, that is the finding.
Applied: CIM analysis .
- Management Presentation PE
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The live session in which the target’s leadership presents the business to shortlisted buyers, usually with its own deck of financial and operational figures.
It is the fourth document the adjusted EBITDA has to match, and the one most often prepared separately from the others.
// HOW IT GETS GAMED
Prepared under time pressure by a different team than the CIM, so figures drift. Drift is then explained verbally in the room, where it leaves no record.
// HOW TO TEST IT
Reconcile the deck to the CIM and the model before the session, and bring the deltas as questions. Ask for written confirmation of any figure explained verbally.
Applied: CIM analysis .
- Confirmatory Diligence PE
-
The detailed verification phase conducted under exclusivity, after price and structure are agreed in principle.
The name states the intent precisely: it confirms. It is not designed to discover.
// HOW IT GETS GAMED
Discovery gets deferred into it because pre-LOI screening was too expensive to run. A confirmatory phase asked to do discovery work under a clock produces re-trades or missed findings, and usually both.
// HOW TO TEST IT
Ask what would have to be true for this phase to find nothing surprising. Anything on that list belongs earlier.
Applied: AI due diligence software .
- Platform Acquisition PE
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The initial acquisition in a buy-and-build strategy, intended as the operating and financial base onto which subsequent add-ons are consolidated.
Diligence errors in the platform do not stay in the platform. They become the baseline every add-on is measured and integrated against.
// HOW IT GETS GAMED
Platform diligence is thorough; the error is in what it inherits. An overstated platform EBITDA sets an inflated benchmark that makes later underperformance read as integration friction.
// HOW TO TEST IT
Fix the platform’s adjusted EBITDA to a ledger-traceable figure before the first add-on closes, and hold every subsequent bridge to the same standard.
Applied: PE due diligence .
- Add-On (bolt-on) PE
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A smaller acquisition consolidated into an existing platform company, typically acquired at a lower multiple than the platform itself.
Add-ons are individually too small to justify a full QoE — which is precisely the exposure, because there are many of them.
// HOW IT GETS GAMED
Not gamed so much as under-examined. Sellers of small businesses are often unadvised and their bridges are informal, which makes errors more likely rather than less.
// HOW TO TEST IT
Standardize a screening protocol applied identically to every add-on regardless of size. Consistency across many small deals matters more than depth on any one.
Applied: AI due diligence software .
- Buy-and-Build (roll-up) PE
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A strategy of acquiring a platform company then consolidating multiple smaller add-ons, aiming to realize multiple arbitrage and operational scale at exit.
The thesis depends on the aggregate adjusted EBITDA being real. Every unexamined bridge is a small error entering a number that will be sold at a large multiple.
// HOW IT GETS GAMED
Error compounds silently. Six add-ons in eighteen months, none individually large enough to justify a QoE, and the aggregate lands in the platform’s exit EBITDA — where a sophisticated buyer’s advisors find it and reprice at their multiple.
// HOW TO TEST IT
Track a running reconciliation of platform-level adjusted EBITDA against ledger-traceable earnings across the whole programme, not deal by deal.
Applied: PE due diligence .
- Covenant PE
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A contractual condition in a credit agreement requiring the borrower to maintain defined financial ratios or refrain from specified actions.
Covenants are the earliest formal warning available on a portfolio company, and the least monitored between reporting dates.
// HOW IT GETS GAMED
The definitions of EBITDA used for covenant testing frequently permit add-backs the buyer would never accept in a purchase price — so a company can be comfortably compliant and structurally deteriorating at once.
// HOW TO TEST IT
Compare the covenant EBITDA definition against your own. Where the credit agreement is more permissive, headroom is overstated by exactly that difference.
Applied: Portfolio monitoring .
- Net Revenue Retention (NRR) VC
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The percentage of recurring revenue retained from existing customers over a period, including expansion and net of contraction and churn.
NRR above 100% is read as proof of product-market fit and underwrites much of a growth multiple.
// HOW IT GETS GAMED
Cohort selection decides the number. Excluding customers who churned within the period, or measuring only customers present at both endpoints, converts a mediocre figure into an excellent one.
// HOW TO TEST IT
Ask for the cohort definition in writing and recompute including every customer present at period start. Then ask for NRR excluding the top ten accounts.
Applied: VC due diligence .
- Liquidation Preference VC
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The contractual right of preferred shareholders to receive proceeds ahead of common shareholders in an exit, often expressed as a multiple of invested capital.
Headline valuation and what common actually clears are different numbers, and the gap widens with every structured round.
// HOW IT GETS GAMED
Participation rights and stacked multiples accumulate quietly across rounds. A headline valuation can be maintained by granting structure instead of price, which preserves the story and transfers the loss to common.
// HOW TO TEST IT
Build the exit waterfall at several exit values, not just the optimistic one, and read what common receives. That number is the real valuation of the equity everyone is being motivated with.
Applied: VC due diligence .
// SEE THE PHYSICS
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