section: Table of Contents

content:
- [Why AI-Powered Deck Evaluation Matters](#why-ai-powered-deck-evaluation-matters)
- [Core Design Principles](#core-design-principles)
- [The 8 Scoring Dimensions](#the-8-scoring-dimensions)
  - [1. Market Attractiveness (15%)](#1-market-attractiveness--15)
  - [2. Traction & Growth (15%)](#2-traction--growth--15)
  - [3. Unit Economics (15%)](#3-unit-economics--15)
  - [4. Go-to-Market Efficiency (10%)](#4-go-to-market-efficiency--10)
  - [5. Product/Tech, USP & Defensibility (15%)](#5-producttech-usp--defensibility--15)
  - [6. Capital Efficiency & Runway (10%)](#6-capital-efficiency--runway--10)
  - [7. Regulatory/Operational Risk (10%)](#7-regulatoryoperational-risk--10)
  - [8. Team (5%) — Placeholder Score](#8-team-5--placeholder-score)
- [Stage-Aware Weighting](#stage-aware-weighting)
- [Gating Rules: Hard Caps That Override Weights](#gating-rules-hard-caps-that-override-weights)
- [Missing Data Handling & the Evidence Coverage Score](#missing-data-handling--the-evidence-coverage-score)
- [Peer Benchmarking Against 6,586 Companies](#peer-benchmarking-against-6586-companies)
- [The Full Evaluation Stack: Beyond the Deck](#the-full-evaluation-stack-beyond-the-deck)
- [Validation: How We Know It Works](#validation-how-we-know-it-works)
- [Before & After: What Better Decks Look Like](#before--after-what-better-decks-look-like)
- [Output Scale & Interpretation](#output-scale--interpretation)
- [Robustness & Guardrails](#robustness--guardrails)
- [Limitations](#limitations)
- [Frequently Asked Questions](#frequently-asked-questions)
- [Formulas & Definitions](#formulas--definitions)
- [Citation & License](#citation--license)

---

source: Unbiased Ventures

domain: startup-investment-evaluation

document: DeckAnalyst Scoring Methodology v1.0


section: Why AI-Powered Deck Evaluation Matters

content:
Venture capital has a consistency problem. When the same pitch deck is shown to five experienced investors, the resulting assessments routinely diverge by 20–30 points on a 100-point scale. This isn't because any individual analyst is wrong — it's because human evaluation is sensitive to presentation order, fatigue, anchoring bias, pattern-matching against recent wins, and the sheer cognitive load of a document that touches market sizing, unit economics, competitive positioning, regulatory risk, and capital efficiency simultaneously.

A senior analyst doing a thorough evaluation of a single pitch deck spends 7–8 hours. They review the deck itself, cross-reference market data, check competitive benchmarks, assess financials, and synthesize across dimensions. The result is high-quality but expensive, slow, and — critically — not reproducible. The same analyst scoring the same deck a month later may arrive at a different number, because their mental benchmark pool has shifted.

DeckAnalyst was built to solve this specific problem: deliver a score that is structurally equivalent to what a senior analyst produces in a full deep dive, but do it in minutes, reproducibly, and across the same dimensions every time. The system doesn't replace human judgment — it provides a consistent, transparent baseline that investors can use to triage, compare, and prioritize.

---

document: DeckAnalyst Scoring Methodology v1.0


section: Core Design Principles

content:
**Score the deck, not the company.** DeckAnalyst evaluates what founders actually present. If critical information is missing from the deck, that's reflected in the score — the system doesn't fill gaps with assumptions or external research. This mirrors how a real analyst operates: the deck is the primary artifact, and omissions are themselves a signal.

**Stage-aware expectations.** A Pre-Seed deck without revenue isn't penalized the same way a Series A deck without revenue would be. Thresholds, weights, and gating rules shift based on stage detection. A great Pre-Seed deck excels on problem clarity, technical insight, and market understanding. A great Series A deck excels on traction, unit economics, and go-to-market repeatability.

**Conservative on missing data.** When a deck omits a key metric, the system doesn't redistribute weight to other dimensions. Instead, the relevant sub-score is capped, and if the missing metric is critical (LTV/CAC, payback, burn/runway), a hard evidence cap is applied to the total score. This prevents decks from achieving high scores simply by omitting their weaknesses.

**Transparent scoring.** Every score comes with a per-dimension breakdown, evidence citations from the deck, and a clear indication of what data was present versus missing. There are no hidden weights or black-box adjustments.

**Team evaluation is a separate discipline.** DeckAnalyst deliberately excludes team and founder assessment from the deck score. Evaluating founders requires dedicated methodologies — structured interviews, psychological trait assessments, and behavioral analysis — that cannot be meaningfully performed by reading a pitch deck. The team dimension carries a placeholder score until purpose-built assessment tools provide real evidence (see [The Full Evaluation Stack](#the-full-evaluation-stack-beyond-the-deck)).

---

document: DeckAnalyst Scoring Methodology v1.0


section: The 8 Scoring Dimensions

content:
DeckAnalyst evaluates pitch decks across 8 dimensions. Seven dimensions are fully scored based on deck evidence. The eighth — Team — carries a conservative placeholder score until dedicated founder assessment tools provide independent evidence.

Each dimension is scored 0–5 and multiplied by its weight. The total score ranges from 0 to 100. Default weights are calibrated for Seed-stage decks and shift for Pre-Seed and Series A (see [Stage-Aware Weighting](#stage-aware-weighting)).

| # | Dimension | Weight | What It Evaluates |
|---|-----------|--------|-------------------|
| 1 | Market Attractiveness | 15% | Market size, growth rate, problem urgency, ICP clarity |
| 2 | Traction & Growth | 15% | ARR/MRR, growth rate, retention, churn, pipeline |
| 3 | Unit Economics | 15% | CAC, LTV, LTV/CAC ratio, payback period, gross margin |
| 4 | Go-to-Market Efficiency | 10% | Repeatability, channel fit, sales cycle, PLG levers |
| 5 | Product/Tech, USP & Defensibility | 15% | Technical edge, competitive differentiation, data moats, IP, switching costs |
| 6 | Capital Efficiency & Runway | 10% | Burn multiple, runway months, milestone plan per € |
| 7 | Regulatory/Operational Risk | 10% | Compliance paths, platform dependencies, certifications |
| 8 | Team *(placeholder)* | 5% | Dummy score — pending dedicated founder assessment |

Total weights sum to 100%. The formula is: **Total Score = Σ (Sub-score × Weight)**.

---

### 1. Market Attractiveness — 15%

**Why this dimension exists:** A startup solving a real problem in a large, growing market has structural tailwinds. A startup solving a marginal problem in a shrinking market has to be exceptional at everything else just to survive. Market attractiveness is weighted at 15% because it's the single largest external factor determining whether a business model can scale.

**What scores well:**
- Total addressable market (TAM) of €1–2B or larger, with a clearly defined serviceable addressable market (SAM).
- Market growth rate of 20%+ CAGR, supported by identifiable structural drivers (regulation, technology shift, demographic change).
- Acute, well-articulated pain points — the problem should be urgent enough that prospects actively seek solutions rather than tolerating the status quo.
- Crisp ideal customer profile (ICP). The deck names who they sell to, why those buyers buy, and what the entry point looks like.

**What scores poorly:**
- "The market is still being created" without evidence of existing demand or analogous markets.
- Vague ICP. If the deck describes its customer as "enterprises" or "SMBs" without segmentation, the market story is incomplete.
- Fragmented markets without a clear beachhead. The deck should show where concentration is possible.

**Why it matters for the overall score:** Market attractiveness interacts with nearly every other dimension. A large, growing market makes unit economics easier (bigger deals, shorter sales cycles), improves capital efficiency (less spend per unit of growth), and increases defensibility (more room for differentiation). A 5/5 here lifts the ceiling on what's possible in every other dimension.

---

### 2. Traction & Growth — 15%

**Why this dimension exists:** Traction is the single strongest evidence that the market hypothesis is correct and the product works. At Seed and beyond, traction separates narrative from reality.

**What scores well:**
- Annual recurring revenue (ARR) of €500K+ at Seed.
- Month-over-month growth of 10%+ or quarter-over-quarter growth of 30%+.
- Net dollar retention (NDR) of 110%+ — existing customers are expanding, not just renewing.
- Logo churn of 3% per month or less.
- A resilient pipeline with committed deals, not just "conversations."

**What scores poorly:**
- Flat or negative growth trajectories.
- High churn rates that require constant new-customer acquisition to maintain revenue.
- "Pilot-driven" traction — multiple proof-of-concepts without conversion to paying customers.

**Stage nuance:** Pre-Seed decks are not expected to show ARR. At Pre-Seed, traction signals shift to waitlists, LOIs, pilot commitments, or validated demand from interviews. The absence of ARR at Pre-Seed is treated as neutral (3/5), not penalized.

---

### 3. Unit Economics — 15%

**Why this dimension exists:** Revenue growth without viable unit economics is a path to larger losses, not a path to a business. This dimension determines whether each customer relationship creates or destroys value.

**What scores well:**
- LTV/CAC ratio of 3× or higher.
- Payback period of 12 months or less (for SaaS).
- Gross margin of 70%+ (software-typical).
- Low implementation/onboarding costs relative to contract value.

**What scores poorly:**
- LTV/CAC below 1.5× — the company is spending nearly as much acquiring customers as it earns from them.
- Payback period exceeding 18–24 months — capital is locked up too long.
- Gross margin below 50% — the business may have structural cost issues that prevent scaling profitably.

**Gating interaction:** LTV/CAC below 1.0 triggers a hard cap of 30 on the total score, regardless of how well other dimensions perform (see [Gating Rules](#gating-rules-hard-caps-that-override-weights)).

---

### 4. Go-to-Market Efficiency — 10%

**Why this dimension exists:** A great product in a great market still fails if it can't be sold repeatably. GTM efficiency measures whether the startup has found a sales motion that works and can scale.

**What scores well:**
- A repeatable sales process — not just founder-led heroics, but a documented, transferable motion.
- Clear channel mix with evidence of what works (inbound, outbound, partnerships, PLG).
- Sales cycle of 90 days or less for SMB/SME, or 180 days or less for mid-market.
- Active customer references that new prospects can speak to.

**What scores poorly:**
- Purely opportunistic deal flow — each deal is a custom effort.
- Only founder-led sales with no plan to build a sales team or scalable motion.
- No evidence of ICP/pricing fit — the deck describes a product without explaining who pays what for it.

---

### 5. Product/Tech, USP & Defensibility — 15%

**Why this dimension exists:** Without defensibility, any initial traction advantage can be competed away. This dimension evaluates whether the startup has built (or is building) durable structural advantages, and how its value proposition stacks up against companies that have already been validated by top accelerators and competitions.

**What scores well:**
- Proprietary data assets that improve with usage (data network effects).
- Meaningful switching costs — customers would face real pain moving to a competitor.
- Patents, trade secrets, or technical barriers that competitors cannot trivially replicate.
- Technical architecture decisions that compound over time (e.g., a data flywheel, compounding ML model performance).
- Clear differentiation versus publicly known finalists and winners from programs such as Techstars, Y Combinator, Alchemist, Plug & Play, de Vigier Prize, Startup Days Switzerland, Venturelab, and Swiss Top 100.

**What scores poorly:**
- Commodity technology stack — the product could be rebuilt by a competent team in months.
- Easily replicated features without underlying structural advantage.
- Critical dependence on a single vendor or API (e.g., a wrapper around a third-party model with no proprietary layer).
- Below-benchmark differentiation compared to similar solutions from validated competitors.

**Competitive benchmarking scoring (0–5):**
- **0–1:** Below benchmark — similar solution with weaker metrics than comparable winners.
- **2–3:** Parity or niche edge — competitive but not clearly differentiated.
- **4:** Clear edge in at least two dimensions (traction, technology, or moat) versus current winner cohorts.
- **5:** Top-decile differentiation profile — the startup would stand out even among recent winners.

---

### 6. Capital Efficiency & Runway — 10%

**Why this dimension exists:** Capital efficiency determines how much progress a startup makes per euro raised. Burn rate without proportional growth is a structural problem, not a growth strategy.

**What scores well:**
- Burn multiple of 1.5× or lower (net burn / net new ARR). This means the company spends €1.50 or less for every €1 of new ARR.
- Runway of 12–18 months — enough time to reach defined milestones before the next raise.
- Clear milestone plan that ties capital deployment to measurable outcomes.

**What scores poorly:**
- Burn multiple exceeding 2.5× — the company is spending far more than it's generating.
- Runway under 9 months without a strong pipeline or imminent close.
- Vague "use of proceeds" — the deck doesn't connect capital to specific milestones.

**Gating interaction:** Burn multiple above 3× combined with less than 9 months of runway triggers a hard cap of 40.

---

### 7. Regulatory/Operational Risk — 10%

**Why this dimension exists:** Some markets carry regulatory requirements that can add years and millions to a startup's timeline. This dimension identifies risks that, if unaddressed, could make the business plan unviable regardless of product or market quality.

**Scoring is inverse:** 5 = low risk, 0 = severe unaddressed risk.

**What scores well (low risk):**
- Clear regulatory approval path with identified milestones.
- Existing certifications or pre-approvals.
- Regulation used as a competitive moat — compliance becomes a barrier to entry.

**What scores poorly (high risk):**
- Medical or financial products without a clear path to required approvals.
- Critical platform dependencies (e.g., business model depends on a single distribution platform's policies).
- Uncalculated compliance costs that could materially affect unit economics.
- No mention of regulatory landscape in a clearly regulated domain.

---

### 8. Team — 5% (Placeholder Score)

DeckAnalyst assigns a conservative placeholder score of 5% weight to the Team dimension. This is a deliberate architectural decision, not an omission.

**Why a placeholder?** Evaluating founders and teams from a pitch deck alone is unreliable. A deck can state credentials and bios, but it cannot reveal psychological resilience, decision-making under pressure, interpersonal dynamics, dark-side personality traits, or founder-market fit at the depth required for investment decisions. Attempting to score these from slide content would produce false confidence.

**How team evaluation actually happens:** Unbiased Ventures has developed dedicated, purpose-built assessment tools that provide rigorous, independent team and founder scoring:

- **Structured Founder Interview** — based on the methodology described in Jaffar et al., a standardized interview protocol that evaluates founder capabilities, vision clarity, and execution orientation through behavioral evidence rather than self-reported credentials.
- **Comprehensive Psychological Assessment** — a multi-instrument assessment battery grounded in established psychometric frameworks including the Hogan Personality Inventory, the Dark Tetrad (narcissism, Machiavellianism, psychopathy, and sadism), and the Big Five personality trait model (openness, conscientiousness, extraversion, agreeableness, neuroticism). This assessment surfaces founder personality profiles, risk factors, and team dynamics that are invisible in a pitch deck.

These assessments produce independent, quantitative team scores that replace the placeholder once completed. The DeckAnalyst score and the team assessment scores are combined in a downstream master scoring layer that produces a complete investment evaluation.

**The key point:** Every aspect of founder and team quality is scored — by tools specifically designed for that purpose, not by a pitch-deck parser attempting to infer psychology from bullet points on a "Team" slide.

---

document: DeckAnalyst Scoring Methodology v1.0


section: Stage-Aware Weighting

content:
The default weights above are calibrated for **Seed stage**. The system detects stage from the deck and adjusts expectations:

**Pre-Seed adjustments:**
- Traction and unit economics weights decrease; technology, product, and problem weights increase.
- Missing revenue metrics are treated as neutral (3/5), not penalized.
- Gating rules around LTV/CAC and payback are relaxed — these metrics typically don't exist yet.

**Series A adjustments:**
- Traction, unit economics, and GTM efficiency weights increase; stricter gating thresholds apply.
- The expectation for repeatable sales motion is much higher — founder-led sales alone is a warning sign at Series A.
- Missing financial metrics are penalized more heavily.

Stage detection is automated based on signals within the deck: stated raise amount, team size, revenue figures, product maturity indicators, and explicit stage labels. When stage is ambiguous, the system defaults to Seed.

---

document: DeckAnalyst Scoring Methodology v1.0


section: Gating Rules: Hard Caps That Override Weights

content:
Regardless of how well a deck performs across other dimensions, certain conditions trigger hard score caps:

| Condition | Maximum Total Score |
|-----------|-------------------|
| LTV/CAC < 1.0 | 30 |
| Payback > 24 months (SaaS) | 40 |
| Burn multiple > 3× with < 9 months runway | 40 |
| No ICP + no paying customer at Seed | 35 (DeepTech exception possible) |
| Legal showstopper risk without a plan | Reject until clarified |

**Why gating rules exist:** Weighted scoring alone can mask fatal flaws. A deck with a brilliant market story (5/5 on market attractiveness) and strong product (5/5) but an LTV/CAC below 1.0 is fundamentally unviable — it loses money on every customer. No amount of excellence elsewhere compensates for that. Gating rules encode the investment realities that no weighting scheme can capture through averaging alone.

**DeepTech exception:** Pre-revenue DeepTech companies at Seed may lack paying customers by the nature of their development cycle (hardware, biotech, deep R&D). The "no ICP + no paying customer" gate can be relaxed when the deck demonstrates clear technical milestones, grant funding, LOIs, or institutional partnerships that validate demand.

---

document: DeckAnalyst Scoring Methodology v1.0


section: Missing Data Handling & the Evidence Coverage Score

content:
### The Problem with Missing Data

Founders sometimes omit metrics from their deck — sometimes because the metrics don't exist yet (legitimate at Pre-Seed), sometimes because the numbers aren't flattering. The scoring system must handle both cases without rewarding omission.

### Design Principles

- **No re-weighting:** Missing data does not shift weight to other dimensions. The dimension is scored at a cap, and the weight stays. This prevents a deck from getting a high score simply by omitting its weakest areas.
- **Conservative caps:** Critical missing fields trigger per-criterion score caps.
- **Evidence caps on total:** When gating-level evidence is missing, the total score is capped regardless of per-dimension performance.
- **Stage-awareness:** Pre-Seed decks are not penalized for metrics that don't typically exist at that stage.

### Per-Criterion Caps (Seed Defaults)

- **Traction & Growth (15%):** Missing ARR and growth data → max 2/5. Missing one → max 3/5. Pre-Seed with no revenue → neutral 3/5.
- **Unit Economics (15%):** Missing churn → max 3/5. Missing CAC → max 3/5. Both missing → max 2/5. Pre-Seed → neutral 3/5.
- **Capital Efficiency (10%):** Missing runway or burn multiple → max 3/5. Both missing → max 2/5.
- **GTM, Product/USP:** Missing core evidence → max 3/5.
- **Regulatory Risk (10%):** Regulated domain without clear path → 2/5. Unregulated domain → neutral 3/5.
- **Product/USP & Defensibility (15%):** Unclear value proposition → max 3/5. Demonstrated parity → 3/5. Documented edge → 4–5.

### Evidence Cap on Total Score

| Missing Evidence | Total Score Cap |
|-----------------|----------------|
| Any one of: LTV/CAC, Payback, Burn Multiple/Runway | ≤ 75 |
| Any two of the above | ≤ 70 |
| All three missing | ≤ 65 |

### The Evidence Coverage Score (ECS)

Every DeckAnalyst report includes an Evidence Coverage Score (ECS) alongside the main score. The ECS is a 0–100 measure of what share of required evidence fields (weighted by importance) the deck actually provides.

A report might read: **"Overall 72 with ECS 66"** — meaning the deck scored 72 overall, but only 66% of required evidence fields were present. This gives investors immediate visibility into how much of the score rests on actual evidence versus the missing-data handling defaults.

The ECS is accompanied by a "what's missing" checklist that names the specific fields the deck should have included. This makes the score actionable — founders know exactly what to add to strengthen their next version.

---

document: DeckAnalyst Scoring Methodology v1.0


section: Peer Benchmarking Against 6,586 Companies

content:
DeckAnalyst doesn't score decks in isolation. Every evaluation includes a peer benchmarking step that compares the startup against a curated database of 6,586 companies, including Y Combinator alumni and graduates of major accelerator programs.

### How Peer Matching Works

The system uses sector and sub-sector classification to identify the most relevant peer group. Matching considers vertical (e.g., FinTech, HealthTech, PropTech), business model (B2B SaaS, marketplace, hardware), and stage. The result is a peer cohort of companies operating in comparable spaces at comparable stages.

### What Peer Benchmarking Adds

- **Relative scoring context:** A 72/100 in enterprise cybersecurity means something different than a 72/100 in consumer social. Peer benchmarking shows where the startup sits relative to companies that investors have already funded and validated.
- **Dimension-level comparison:** The report shows not just an overall peer percentile, but how the startup compares on each individual dimension — exposing which areas are above-peer and which lag.
- **Competitive landscape signal:** The peer set itself tells a story. A startup in a space where peer companies are consistently well-funded and well-tracted faces a higher bar. A startup in an underserved vertical with few quality peers may have a clearer path.

### Known Limitations of Peer Matching

Peer matching works best when the startup's sector has sufficient representation in the database. In very niche or emerging verticals, the peer set may be small or only loosely analogous. The system flags when peer density is low so investors know to interpret relative metrics with appropriate context.

---

document: DeckAnalyst Scoring Methodology v1.0


section: The Full Evaluation Stack: Beyond the Deck

content:
DeckAnalyst is one layer in a multi-layer investment evaluation methodology. The pitch deck score answers the question: *"How strong is the investment case as presented in this document?"* But a complete investment decision requires evaluating the founders and team independently, with tools purpose-built for that task.

### Why Team Evaluation Is Separate

Pitch decks are inherently self-reported marketing documents. A "Team" slide lists credentials, but credentials alone don't predict execution. The qualities that determine whether a founding team can actually build a venture-scale company — psychological resilience, decision-making under uncertainty, interpersonal dynamics, risk of derailing personality traits, and the depth of founder-market fit — require dedicated assessment methodologies that go far beyond what any document analysis can provide.

### The Dedicated Assessment Tools

Unbiased Ventures has developed and deployed purpose-built tools for founder and team evaluation:

**Structured Founder Interview (Jaffar et al.):** A standardized, evidence-based interview protocol that evaluates founders on execution orientation, vision clarity, adaptability, and domain mastery. The interview is scored quantitatively and produces a founder capability profile that is independent of the pitch deck score.

**Comprehensive Psychological Assessment:** A multi-instrument assessment battery that draws on established, peer-reviewed psychometric frameworks:
- **Hogan Personality Inventory** — measures normal personality characteristics that predict workplace performance and leadership effectiveness.
- **Dark Tetrad Assessment** — screens for narcissism, Machiavellianism, psychopathy, and sadism — personality traits that are associated with founder derailment risk and toxic team dynamics.
- **Big Five Personality Traits** — evaluates openness, conscientiousness, extraversion, agreeableness, and neuroticism — the most widely validated model of personality structure in contemporary psychology.

These assessments are administered, scored, and interpreted through dedicated tools developed specifically for the startup investment context. They produce quantitative team and founder scores that integrate with the DeckAnalyst score in a master scoring layer.

### The Master Score

The complete Unbiased Ventures evaluation produces a **Master Score** that combines the DeckAnalyst pitch-deck score, the structured interview score, and the psychological assessment score. This master score reflects both the strength of the business case (as presented in the deck) and the quality of the team behind it — each evaluated by the methodology best suited to that domain.

No aspect of the investment decision is left to informal impression. The deck is scored by DeckAnalyst. The founders are scored by dedicated interview and psychometric tools. The combined result is a comprehensive, transparent, and reproducible investment evaluation.

---

document: DeckAnalyst Scoring Methodology v1.0


section: Validation: How We Know It Works

content:
### The Calibration Process

DeckAnalyst's scoring methodology was developed over 12+ months of iterative research and calibration. The process involved parallel development tracks, each lasting a minimum of six months, focused on refining dimension definitions, weight allocations, gating thresholds, and missing-data handling.

### Human Analyst in the Loop

Validation was conducted by a senior investment analyst who works for Techstars as senior analyst and lead evangelist of the Techstars methodology, and who also works with the Founder Institute by The Decile Group. This is a practitioner who evaluates pitch decks professionally, at scale, using established institutional frameworks.

The validation protocol:
- **Seven sample decks** from **seven different industries** were selected to cover the range of sectors, stages, and quality levels DeckAnalyst encounters.
- Each deck was independently scored by the human analyst using a full deep-dive process (7–8 hours per deck).
- DeckAnalyst scored the same decks.
- Scores were compared on a weekly basis throughout the development cycle.
- Discrepancies were analyzed at the dimension level to identify where the system's logic needed refinement.
- The process iterated: when human and machine scores diverged on a dimension, the underlying scoring logic, thresholds, or evidence extraction was adjusted and re-tested.

### What "Alignment" Means

The target was not perfect agreement — even experienced human analysts don't agree with each other perfectly. The target was that DeckAnalyst's scores fall within the range of professional analyst variance. In practice, this means the system's score on a given deck is as close to the human analyst's score as two human analysts would typically be to each other.

This framing is important: the goal is not to replace human judgment but to provide a consistent, reproducible baseline that operates within the bounds of professional-quality analysis.

---

document: DeckAnalyst Scoring Methodology v1.0


section: Before & After: What Better Decks Look Like

content:
### Example 1: Market Attractiveness

**Before (Score: 2/5):**
> "We're building the future of work. The market is massive — remote work is everywhere. Everyone needs our product."

No TAM figure, no SAM, no CAGR, no ICP, no articulation of specific pain point. The claim is vague and unsupported.

**After (Score: 4/5):**
> "The European SMB HR-tech market is €4.2B (Statista 2024), growing at 22% CAGR driven by regulatory complexity post-EU AI Act. Our ICP is 50–200 employee companies in DACH with distributed teams. Their #1 pain: compliance across 3+ jurisdictions costs €180K/year in legal fees they can't afford."

TAM sourced and sized, CAGR cited with structural driver, ICP crisp, pain point quantified, beachhead named.

### Example 2: Unit Economics

**Before (Score: 1/5):**
> "We're growing fast and costs will come down at scale."

No CAC, no LTV, no margin, no payback. The deck asserts future efficiency without evidence.

**After (Score: 4/5):**
> "CAC is €2,400 (blended inbound/outbound), LTV is €14,400 (€400/mo × 82% gross margin × 36-month avg. lifetime), LTV/CAC is 6.0×, payback is 7.3 months. Inbound CAC trending down 12% QoQ as content flywheel matures."

Every metric defined, LTV formula transparent, trends shown, channel mix visible.

### Example 3: Traction & Growth

**Before (Score: 2/5):**
> "We have strong interest from several Fortune 500 companies and a growing pipeline."

No revenue figures, no growth rate, no retention, no conversion from pipeline.

**After (Score: 5/5):**
> "€620K ARR, 14% MoM growth over last 6 months. NDR 118%. Logo churn 1.8%/month. Pipeline: €340K committed (signed LOIs), €210K best-case. 3 Fortune 500 pilots converting to annual contracts in Q1 (€45K ACV avg)."

Concrete numbers, growth quantified, retention demonstrated, pipeline staged by confidence level.

### Example 4: Regulatory Risk

**Before (Score: 1/5):**
> "We operate in healthcare. Regulations exist but we'll figure them out."

Regulated domain acknowledged but no path, no timeline, no cost estimate.

**After (Score: 4/5):**
> "Class IIa medical device under EU MDR. Pre-submission meeting with notified body (BSI) completed March 2024. Clinical evaluation report in progress — CER expected Q3 2024. Regulatory budget: €280K allocated. CE marking target: Q1 2025. Regulatory moat: competitors are 18–24 months behind on MDR compliance."

Clear approval path, milestones dated, costs budgeted, compliance positioned as competitive advantage.

---

document: DeckAnalyst Scoring Methodology v1.0


section: Output Scale & Interpretation

content:
| Score Range | Interpretation |
|-------------|---------------|
| 80–100 | **Top-Tier — Investable.** The deck presents a compelling case across all major dimensions. Proceed to founder assessment and deeper due diligence. |
| 65–79 | **Track / Build a Case.** Strong in several dimensions but gaps remain. Consider smaller initial tickets, milestone-based tranches, or further diligence on weak areas. Founder assessment may elevate or confirm concerns. |
| 50–64 | **High Uncertainty.** The deck shows promise in some areas but critical dimensions are underdeveloped. Wait for specific milestones before committing. |
| Below 50 | **Not Investable for Now.** Fundamental gaps in multiple dimensions. The startup may need to iterate on product, market, or business model before seeking this stage of investment. |

These ranges are calibrated against the human analyst's scoring distribution. A score of 80+ from DeckAnalyst corresponds to decks that the human analyst would flag as top-tier candidates for immediate deeper diligence.

---

document: DeckAnalyst Scoring Methodology v1.0


section: Robustness & Guardrails

content:
### Hallucination Control

DeckAnalyst scores are derived exclusively from evidence present in the submitted deck. The system uses a retrieval-augmented generation (RAG) architecture where every claim must be traceable to specific text or data in the source document. An independent evidence auditor layer validates each dimension's score against the extracted evidence, flagging cases where a score assertion isn't supported by the underlying content.

When section-specific evidence extraction returns empty (e.g., the deck has no dedicated financials slide), the system falls back to full-text search across the entire document before defaulting to missing-data caps. This prevents legitimate evidence from being missed due to non-standard deck structures.

### Determinism & Reproducibility

Scoring uses controlled generation parameters to minimize run-to-run variance. The target is that the same deck, scored multiple times, produces scores within a narrow band — tight enough that the variance is smaller than the margin of error between two human analysts scoring the same deck.

### Prompt Injection Resistance

DeckAnalyst processes untrusted documents — pitch decks submitted by founders. The system includes guardrails against prompt injection attempts embedded in deck content. The scoring pipeline treats deck text as data to be evaluated, not as instructions to be followed. The specifics of these guardrails are not published to avoid providing a roadmap for circumvention.

### Drift Prevention

The scoring methodology is versioned and locked. Changes to dimension definitions, weight allocations, gating thresholds, or evidence handling require explicit versioning and re-validation against the reference deck set. This prevents gradual drift in scoring behavior over time.

---

document: DeckAnalyst Scoring Methodology v1.0


section: Limitations

content:
**DeckAnalyst scores the deck, not the company.** The system can only evaluate what's presented. A mediocre deck from a strong company will score lower than the company deserves. A polished deck from a weak company may score higher. The score is a measure of how well the investment case is presented, not an oracle about the company's future.

**Peer benchmarking has a ceiling in niche sectors.** When the peer database has limited representation in a specific vertical, relative scoring is less informative. The system flags low peer density but cannot generate comparables that don't exist.

**Stage detection is heuristic.** The system infers stage from deck signals. Occasionally, a deck may be ambiguous (e.g., a Pre-Seed company raising a Seed-sized round). In ambiguous cases, the system defaults to Seed, which may under- or over-penalize certain metrics.

**Language support covers major European languages.** DeckAnalyst reliably scores pitch decks in English, German, Spanish, French, and Italian. Decks in other languages may produce less reliable results.

**The deck score is one input, not the complete picture.** DeckAnalyst produces the deck-analysis layer of the investment evaluation. The complete Unbiased Ventures methodology combines the deck score with independent founder interview scores (Jaffar et al.) and comprehensive psychological assessments (Hogan, Dark Tetrad, Big Five) to produce a master score. Factors that a deck cannot capture — founder psychology, team dynamics, interpersonal risk factors — are evaluated by these dedicated tools, not left to informal judgment.

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document: DeckAnalyst Scoring Methodology v1.0


section: Frequently Asked Questions

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### How does DeckAnalyst differ from a human analyst reviewing a pitch deck?

A senior analyst typically spends 7–8 hours on a comprehensive deck evaluation, reviewing market data, checking competitive benchmarks, assessing financials, and synthesizing across dimensions. DeckAnalyst performs a structurally equivalent analysis in minutes, across the same dimensions, with the same gating rules and stage-aware thresholds. The key difference is consistency: the system produces the same score for the same deck regardless of time of day, order in the review queue, or analyst fatigue. The tradeoff is that a human analyst can incorporate context that isn't in the deck — industry relationships, unpublished market intelligence — that an automated system cannot. For founder and team quality, DeckAnalyst defers to dedicated assessment tools rather than attempting to infer psychology from a "Team" slide.

### Why 8 dimensions? Why these specific ones?

The 7 fully-scored dimensions were selected through iterative research to cover the complete set of factors that professional investors evaluate when assessing an early-stage company's business case from its pitch deck. Each dimension was validated independently: removing any single dimension produced scores that diverged from human analyst assessments in predictable, explainable ways — confirming that each dimension carries unique information. The eighth dimension — Team — is held as a placeholder because team evaluation requires methodologies fundamentally different from document analysis. Dedicated psychological and interview-based tools handle that domain.

### Can founders "game" the scoring system?

Publishing the methodology transparently means founders know what's being evaluated. But "gaming" the system means presenting strong evidence across all dimensions — which is functionally equivalent to building a strong investment case. A deck that scores well on DeckAnalyst is a deck that presents clear market sizing, demonstrated traction, viable unit economics, a defensible product, and responsible capital management. If a founder "games" the system by adding all of that to their deck, they've simply written a better deck.

The system's anti-gaming defense is that it scores evidence, not claims. Stating "our LTV/CAC is 5×" without supporting data is scored differently than presenting the underlying metrics that demonstrate it. Gating rules and the Evidence Coverage Score further limit the ability to inflate scores through narrative alone.

### How often is the peer benchmark database updated?

The peer database is maintained and expanded on an ongoing basis. As of the current version, it contains 6,586 companies sourced from Y Combinator, major accelerator programs, and publicly available competition results. New cohorts are added as they become available. The benchmarking methodology and sector classification are versioned alongside the scoring system.

### What if my deck doesn't fit standard formats?

DeckAnalyst uses full-text fallback when section-specific extraction returns empty. Non-standard deck structures — decks without dedicated market slides, or with information distributed across narrative sections rather than labeled slides — are still processed. The system searches the entire document for evidence relevant to each dimension. However, decks with clear, well-labeled sections tend to score more accurately because the evidence extraction is more precise.

### What languages does DeckAnalyst support?

DeckAnalyst reliably scores pitch decks in English, German, Spanish, French, and Italian. These cover the major European startup ecosystems. Support for additional languages may be added based on demand.

### How does the team evaluation work if it's not in the deck score?

DeckAnalyst assigns a 5% placeholder for the Team dimension. The real team score comes from dedicated assessment tools developed specifically for founder evaluation: a structured interview protocol (Jaffar et al.) and a comprehensive psychological assessment battery (Hogan, Dark Tetrad, Big Five). These produce independent, quantitative scores that replace the placeholder in the master scoring layer. This separation ensures that team quality is evaluated with the rigor it deserves, using the right tools for the job.

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document: DeckAnalyst Scoring Methodology v1.0


section: Formulas & Definitions

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| Metric | Formula |
|--------|---------|
| **LTV (Simplified)** | Average monthly revenue × Gross margin × (1 / Monthly churn rate) |
| **LTV/CAC** | LTV ÷ Customer acquisition cost |
| **Payback Period (months)** | CAC ÷ Monthly contribution margin per customer |
| **Burn Multiple** | Net burn ÷ Net new ARR (quarterly or 12-month rolling) |
| **Net Dollar Retention (NDR)** | (ARR of cohort at t₁ / ARR of same cohort at t₀) × 100 |
| **Evidence Coverage Score (ECS)** | (Weighted sum of evidenced required fields / Total weighted required fields) × 100 |

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document: DeckAnalyst Scoring Methodology v1.0


section: Citation & License

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This methodology guide is published by **Unbiased Ventures** and is made available under the [Creative Commons Attribution 4.0 International License (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/).

You are free to share and adapt this material for any purpose, including commercial use, provided appropriate credit is given.

**Suggested citation:**

> Unbiased Ventures. "How DeckAnalyst Scores a Pitch Deck: The Complete Methodology." Published at unbiasedventures.ch.

For questions about the methodology, commercial API access, or partnership inquiries, visit [unbiasedventures.ch](https://unbiasedventures.ch) or email [deckanalyst@unbiasedventures.ch](mailto:deckanalyst@unbiasedventures.ch).

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*Last updated: June 2026 · Version: 1.0*

document: DeckAnalyst Scoring Methodology v1.0