TOOL
Power Map

Where does durable Power appear to reside?

This page derives Power hypotheses from the Company Model, active Experience, Key Debates, and attached evidence. It keeps thesis strength separate from evidence strength and does not compute an overall moat score.

Structured assessment, not empirical measurement.

This Lab represents, measures, stress-tests, and can falsify the Compounding Expertise thesis. Scores are explicit judgments with evidence provenance, not validated moat measurements.

Current Power conclusion

No durable Power is currently demonstrated by available evidence.

Graded capture is supported in the selected cases. Learning improvement, transfer, and resistance to reconstruction remain to be tested.

UNPROVEN MECHANISM

Power fingerprint

Scale Economies

Fixed-cost leverage or declining unit costs with scale.

ThesisUNPROVEN
EvidenceNONE
Network Economies

Cross-customer experience improves value for other customers.

ThesisUNPROVEN
EvidenceNONE
Counter-Positioning

Incumbents cannot respond without damaging their existing business.

ThesisUNPROVEN
EvidenceNONE
Switching Costs

Accumulated customer context, integrations, or workflow dependency make replacement costly.

ThesisUNPROVEN
EvidenceNONE
Branding

Trust or reputation reduces buyer uncertainty or supports willingness to pay.

ThesisUNPROVEN
EvidenceNONE
Cornered Resource

Scarce privileged data, rights, or relationships are hard for challengers to access.

ThesisUNPROVEN
EvidenceNONE
Process Power

Closed learning/update/deploy routines compound into hard-to-copy operating performance.

ThesisUNPROVEN
EvidenceLOW

Power mechanism map

Cross-customer transfer→Network EconomiesUNPROVEN thesis · NONE evidence
Learning causality + closed loop→Process PowerUNPROVEN thesis · LOW evidence
Customer-specific accumulated state→Switching CostsUNPROVEN thesis · NONE evidence
Privileged experience + rights→Cornered ResourceUNPROVEN thesis · NONE evidence

Power cards

HELMER POWER

Scale Economies

Thesis UNPROVENEvidence NONE
ThesisUNPROVEN
EvidenceNONE

Mechanism: Fixed-cost leverage or declining unit costs with scale.

Why: No direct unit-cost or fixed-cost leverage evidence is attached.

Unit cost decline

UNPROVENNONE evidence

Shared infrastructure leverage

UNPROVENNONE evidence

Analyst assessment

0/5 · LOW confidence · UNKNOWN

Public evidence analysis starts from sourced public records and explicit unknowns. No production case-level data has been loaded.

Full evidence

Evidence for

No evidence in this category yet.

Evidence against

No evidence in this category yet.

Missing evidence

No evidence in this category yet.

Relevant debates: None attached yet.

HELMER POWER

Network Economies

Thesis UNPROVENEvidence NONE
ThesisUNPROVEN
EvidenceNONE

Mechanism: Cross-customer experience improves value for other customers.

Why: The full company-level thesis is not yet resolved. Insufficient held-out coverage No applied synthetic mechanism result is attached to this dataset.

Cross-customer transfer

UNPROVENNONE evidence

Pooling rights

UNPROVENLOW evidence

Feedback velocity

UNPROVENNONE evidence

Analyst assessment

0/5 · LOW confidence · UNKNOWN

Public evidence analysis starts from sourced public records and explicit unknowns. No production case-level data has been loaded.

Full evidence

Evidence for

Experience → active CaseSet

0/0 decision-class/case-type patterns occur across segments; 0/0 eligible cases belong to shared patterns.

Measures whether segments share potentially reusable decision structure.

Limitation: Shared structure is a prerequisite for transfer, not its performance result.

Inspect source
Experience → active CaseSet

Insufficient held-out coverage. 0 held-out cases; local Brier unavailable, pooled unavailable.

Segment transfer probe v1: earliest 70% train, latest 30% test; only feedback available before each test decision is used. Predict CORRECT versus other resolved grades from decision class and case type. Same fixed smoothing in each arm; lower Brier score is better. A 0.005 Brier difference defines the descriptive effect band, not statistical significance.

Limitation: Groups are customer segments, not identified customers. This tests transfer of grade prediction; improving chosen actions requires an action-policy experiment.

Inspect source

Evidence against

No evidence in this category yet.

Missing evidence

Experience → action-policy experiment

Insufficient grade-prediction coverage; decision-policy improvement remains untested.

Use identified customers and compare local versus pooled policies on held-out decisions, measuring correctness and economic outcomes.

Limitation: Missing evidence cannot support the proposition.

Relevant debates: CROSS_CUSTOMER_TRANSFER

HELMER POWER

Counter-Positioning

Thesis UNPROVENEvidence NONE
ThesisUNPROVEN
EvidenceNONE

Mechanism: Incumbents cannot respond without damaging their existing business.

Why: No incumbent conflict or cannibalization evidence is attached.

Incumbent conflict

UNPROVENNONE evidence

Business-model incompatibility

UNPROVENNONE evidence

Analyst assessment

0/5 · LOW confidence · UNKNOWN

Public evidence analysis starts from sourced public records and explicit unknowns. No production case-level data has been loaded.

Full evidence

Evidence for

No evidence in this category yet.

Evidence against

No evidence in this category yet.

Missing evidence

No evidence in this category yet.

Relevant debates: None attached yet.

HELMER POWER

Switching Costs

Thesis UNPROVENEvidence NONE
ThesisUNPROVEN
EvidenceNONE

Mechanism: Accumulated customer context, integrations, or workflow dependency make replacement costly.

Why: No switching-cost mechanism is evidenced yet.

Accumulated customer context

UNPROVENNONE evidence

Integration depth

WEAKNONE evidence

Replacement performance gap

UNPROVENNONE evidence

Analyst assessment

0/5 · LOW confidence · UNKNOWN

Public evidence analysis starts from sourced public records and explicit unknowns. No production case-level data has been loaded.

Full evidence

Evidence for

No evidence in this category yet.

Evidence against

No evidence in this category yet.

Missing evidence

No evidence in this category yet.

Relevant debates: None attached yet.

HELMER POWER

Branding

Thesis UNPROVENEvidence NONE
ThesisUNPROVEN
EvidenceNONE

Mechanism: Trust or reputation reduces buyer uncertainty or supports willingness to pay.

Why: No willingness-to-pay or trust evidence is attached.

Trust / reputation

UNPROVENNONE evidence

Willingness to pay

UNPROVENNONE evidence

Analyst assessment

0/5 · LOW confidence · UNKNOWN

Public evidence analysis starts from sourced public records and explicit unknowns. No production case-level data has been loaded.

Full evidence

Evidence for

No evidence in this category yet.

Evidence against

No evidence in this category yet.

Missing evidence

No evidence in this category yet.

Relevant debates: None attached yet.

HELMER POWER

Cornered Resource

Thesis UNPROVENEvidence NONE
ThesisUNPROVEN
EvidenceNONE

Mechanism: Scarce privileged data, rights, or relationships are hard for challengers to access.

Why: The full company-level thesis is not yet resolved. Need at least 20 training, 10 validation and 20 final-test cases with chronologically available grades; found 0/0/0. At least 10 grades must be available before validation and 20 before final evaluation. No applied synthetic mechanism result is attached to this dataset.

Exclusive cases/outcomes

UNPROVENNONE evidence

Learning rights

UNPROVENNONE evidence

Resistance to reproduction

UNPROVENLOW evidence

Analyst assessment

0/5 · LOW confidence · UNKNOWN

Public evidence analysis starts from sourced public records and explicit unknowns. No production case-level data has been loaded.

Full evidence

Evidence for

Experience → active CaseSet

Reconstruction has not been tested: no challenger with restricted data access or a calibration budget has been evaluated.

The grade-prediction models share historical data access. Their scores cannot establish how cheaply a competitor could reproduce the capability.

Limitation: Compare against a challenger restricted to public features, rules and a fixed calibration budget.

Inspect source
Company Model → Competitive Architecture

Relearning difficulty: UNKNOWN

Frames the rebuildability hypothesis.

Limitation: Assumption is not a challenger benchmark.

Inspect source

Evidence against

No evidence in this category yet.

Missing evidence

Contracts / data governance

No sourced contractual rights evidence.

Need retention, derived-feature, evaluation, and cross-customer training rights.

Limitation: Missing evidence cannot support the proposition.

Future challenger benchmark

No compression/relearning benchmark.

Need evidence that a capable challenger cannot reproduce performance cheaply.

Limitation: Missing evidence cannot support the proposition.

Relevant debates: LEARNING_RIGHTS, REBUILDABILITY_COMPRESSION

HELMER POWER

Process Power

Thesis UNPROVENEvidence LOW
ThesisUNPROVEN
EvidenceLOW

Mechanism: Closed learning/update/deploy routines compound into hard-to-copy operating performance.

Why: The full company-level thesis is not yet resolved. Need at least 20 training, 10 validation and 20 final-test cases with chronologically available grades; found 0/0/0. At least 10 grades must be available before validation and 20 before final evaluation. No applied synthetic mechanism result is attached to this dataset.

Capture

MODERATEMEDIUM evidence

Grade

UNPROVENNONE evidence

Update

UNPROVENLOW evidence

Deploy

UNPROVENLOW evidence

Reproducibility

UNPROVENLOW evidence

Analyst assessment

0/5 · LOW confidence · UNKNOWN

Public evidence analysis starts from sourced public records and explicit unknowns. No production case-level data has been loaded.

Full evidence

Evidence for

Casap homepage / product materials

Purpose-built AI agents and dispute-management software for banks, credit unions, and fintechs; public materials describe dispute model/API, win-score prediction, fraud functionality, and built-in Reg E, Reg Z, Nacha, and card-network expertise.

Public-source evidence record for the Casap Public Evidence Analysis. Treat as sourced context for diligence, not production case-level evidence.

Limitation: Confidence: MEDIUM. Review source scope before treating as decisive.

Inspect source
Casap Raises $25M Series A

$25M Series A announced August 7, 2025; $33.5M total funding; AI agents analyze evidence, predict outcomes, and automate lifecycle from intake to chargeback filing; proprietary first-party fraud score; company-reported customer results.

Public-source evidence record for the Casap Public Evidence Analysis. Treat as sourced context for diligence, not production case-level evidence.

Limitation: Confidence: MEDIUM. Review source scope before treating as decisive.

Inspect source
Casap Chartway customer story

Company-published customer story reports estimated $875K annual savings, resolution time improved from 90 days to 12 days, 95% chargeback win rate, writeoffs down 72%, costs down 85%, and monthly capacity from 1,200 to 4,000 transactions.

Public-source evidence record for the Casap Public Evidence Analysis. Treat as sourced context for diligence, not production case-level evidence.

Limitation: Confidence: MEDIUM. Review source scope before treating as decisive.

Inspect source
Casap MidSouth customer story

Company-published customer story reports fraud loss reduced 51%, cost per dispute reduced 90%+ from $37, chargeback floor reduced 85%, real-time merchant-response/chargeback tracking, and Visa transaction metadata used in fraud investigation.

Public-source evidence record for the Casap Public Evidence Analysis. Treat as sourced context for diligence, not production case-level evidence.

Limitation: Confidence: MEDIUM. Review source scope before treating as decisive.

Inspect source
Filene Research Institute, 2025 FiLab Results: Casap

Filene Research Institute public report summary describes testing Casap's fraud dispute platform in sandbox and live environments, with participating credit unions reporting usability, reduced manual effort, and confidence supporting compliance/dispute outcomes.

Public-source evidence record for the Casap Public Evidence Analysis. Treat as sourced context for diligence, not production case-level evidence.

Limitation: Confidence: HIGH. Review source scope before treating as decisive.

Inspect source
Filene blog: Chartway Credit Union saved an estimated $875K in one year testing Casap

Filene reports testing Casap with five credit unions; one institution had been live on the platform for more than a year; staff reported a 122% improvement in ease of use versus prior systems; reported dispute-processing error frequency declined 63%.

Public-source evidence record for the Casap Public Evidence Analysis. Treat as sourced context for diligence, not production case-level evidence.

Limitation: Confidence: HIGH. Review source scope before treating as decisive.

Inspect source
Casap October 2024 funding announcement

Company funding announcement claims Casap's platform becomes more effective at fraud detection with customer interaction.

Public-source evidence record for the Casap Public Evidence Analysis. Treat as sourced context for diligence, not production case-level evidence.

Limitation: Confidence: MEDIUM. Review source scope before treating as decisive.

Inspect source
Casap Privacy Policy

Privacy policy says Casap may use collected information to develop/improve products and conduct analytics, including aggregated non-specific information. It also says third-party personal data uploaded through the service is processed on behalf of customers and according to their instructions.

Public-source evidence record for the Casap Public Evidence Analysis. Treat as sourced context for diligence, not production case-level evidence.

Limitation: Confidence: MEDIUM. Review source scope before treating as decisive.

Inspect source
Primary Venture Partners insights

Primary Venture Partners public materials identify Casap in its portfolio/insights context and state Primary led the seed round and invested in every round.

Public-source evidence record for the Casap Public Evidence Analysis. Treat as sourced context for diligence, not production case-level evidence.

Limitation: Confidence: LOW. Review source scope before treating as decisive.

Inspect source
Experience → active CaseSet

Need at least 20 training, 10 validation and 20 final-test cases with chronologically available grades; found 0/0/0. At least 10 grades must be available before validation and 20 before final evaluation.

Tests whether past experience predicts grades on later cases. It does not measure improvement from choosing different actions.

Limitation: Compare decisions made with and without the selected learner on a new evaluation batch.

Inspect source
Experience → active CaseSet

Correct-grade rate: early unavailable, late unavailable.

Descriptive time shift may reflect case mix, policy or grading changes; it is not attributed to learning.

Limitation: Compare matched decision types across time and identify policy/model versions.

Inspect source
Experience → active CaseSet

0/0 graded cases.

Grades exist to learn from if connected to updates.

Limitation: Grade coverage does not establish that grades improve future decisions.

Inspect source
Experience → active CaseSet

Need at least 20 training, 10 validation and 20 final-test cases with chronologically available grades; found 0/0/0. At least 10 grades must be available before validation and 20 before final evaluation.

A fixed-test learning curve measures whether additional historical cases help this estimator; results may be non-monotonic.

Limitation: Repeat on a fresh time window and examine changing case mix.

Inspect source
Experience → active CaseSet

0 cases. UNAVAILABLE; UNAVAILABLE; UNAVAILABLE.

Pattern diversity and cohort novelty describe the supply of new information available to learn from.

Limitation: A held-out learning curve is needed to connect novelty to performance gain.

Inspect source
Company Model → Learning Loop

Update: UNKNOWN; deploy: UNKNOWN

Closed-loop architecture is relevant but does not prove difficult-to-copy Process Power.

Limitation: This is deterministic Power Map input, not a standalone proof of durable Power.

Inspect source

Evidence against

No evidence in this category yet.

Missing evidence

Company Model → Learning Loop → UPDATE

UNKNOWN

No evidence currently shows that grades alter future model or policy behavior.

Limitation: Missing evidence cannot support the proposition.

Company Model → Learning Loop → DEPLOY

UNKNOWN

No evidence currently shows learned improvements reach production.

Limitation: Missing evidence cannot support the proposition.

Experience → learning comparison

No controlled before/after learning comparison.

Compare held-out decisions with and without updates from accumulated grades.

Limitation: Missing evidence cannot support the proposition.

Future challenger benchmark

No compression/relearning benchmark.

Need evidence that a capable challenger cannot reproduce performance cheaply.

Limitation: Missing evidence cannot support the proposition.

Relevant debates: EXPERIENCE_CAPTURE, LEARNING_CAUSALITY, REBUILDABILITY_COMPRESSION

Framework provenance

HELMER

Hamilton Helmer Seven Powers. Strategic interpretation layer, not a claim that Compounding Expertise is automatically an eighth Power.

SUN

Ben Sun Compounding Expertise dimensions. These test the scorebook and capture-loop thesis.

WOLFE

David Wolfe extensions. These stress-test transferability, compressibility, causality, nonstationarity, and learning velocity.

Analyst override / advanced assessment

Existing manual SUN / WOLFE / HELMER assessments remain editable for backward compatibility. They are treated as analyst judgment, not as a silent replacement for CE-derived Power evidence.

Is valuable expertise being created?

Does each case teach something decision-relevant, economically meaningful, and causally interpretable?

Objective gradingDecisions can be graded against outcomes with relatively low ambiguity.SUN
Economic value of being rightBetter decisions create meaningful customer or company value.SUN
Marginal information gainNew cases still teach something non-obvious rather than repeating known patterns.WOLFE
Causal qualityThe scorebook distinguishes causality from correlation or confounded outcomes.WOLFE
Does the expertise compound?

Does feedback arrive fast enough, remain fresh, cover edge cases, and transfer across customers?

Feedback speedThe system receives outcome feedback quickly enough to learn.SUN
FreshnessRecent cases remain available and relevant to future decisions.SUN
Cross-customer learningLearning from one customer can improve decisions for others.SUN
Diversity / edge casesThe scorebook includes enough varied and rare cases to improve judgment.SUN
Cross-customer transferabilityExperience transfers across customers without being too context-specific.WOLFE
Customer heterogeneityCustomer variation is understood rather than averaging away important differences.WOLFE
NonstationarityThe environment changes slowly enough, or the learning loop is fast enough, to stay relevant.WOLFE
Learning efficiencyThe organization turns graded cases into product improvement quickly.WOLFE
Is the expertise defensible?

Can competitors reproduce, compress, infer, or legally access the useful learning loop?

Workflow / capture positionThe product sits where decisions and outcomes are naturally captured.SUN
Contractual rights / consentThe company can legally use feedback to improve the product.SUN
Knowledge compressibilityUseful information cannot be easily compressed into a static playbook or prompt.WOLFE
Helmer manual assessments
Scale EconomiesUnit economics improve with volume in a way that is hard to match.HELMER
Network EconomiesProduct value increases as more participants join.HELMER
Counter-PositioningThe model is hard for incumbents to copy without damaging their existing business.HELMER
Switching CostsCustomers face meaningful cost, risk, or disruption when leaving.HELMER
BrandingBrand meaning lowers acquisition friction or supports pricing power.HELMER
Cornered ResourceThe company controls a scarce asset not generally available to rivals.HELMER
Process PowerOperational routines compound into difficult-to-copy performance.HELMER
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