Market intelligence
Similar credentials.
Different exposure.
How to price the difference.
GWK's independent analysis assigns IEQ 2.2 to hubspot.com and 35.7 to freshworks.com. Separately, the article shows how to convert an exposure difference into value, using hypothetical economic scenarios with explicit assumptions.
GWK's independent analysis assigns IEQ 2.2 to hubspot.com and 35.7 to freshworks.com. These scores measure the cryptographic exposure of the observed domains under GWK methodology. They add a quantitative dimension to the comparison of two businesses that disclose conventional security credentials.
Separately, the article converts that exposure distinction into value using two hypothetical scenarios with the same revenue base and migration expenditure. The result depends on stated assumptions: a 10% probability of a cryptographic event over three years and a net loss of 5% of revenue at IEQ 35.7. Under those assumptions the difference ranges from zero to US$12.98 million in present value, depending on how strongly loss follows the score; at the midpoint it is US$10.40 million. The calculation is linear: at the upper bound it is about US$3.5 million per US$1 billion of annual revenue, and doubling the assumed probability or loss doubles the result. Readers can substitute their own assumptions; the method is the contribution, not a single figure.
Similar credentials. Distinct exposure.
In the second quarter of 2026, HubSpot's revenue grew 20% year over year and Freshworks' grew 16%. Operating cash flow represented approximately 24.4% and 24.7% of revenue, respectively. Both disclose SOC 2 Type II reports through their trust centers. Growth, cash generation and security assurance therefore provide common starting points for the comparison.
Sources: HubSpot · results; Freshworks · results; HubSpot · Trust Center; Freshworks · Trust Center.
Domain exposure under GWK methodology.
Independent GWK analysis · domain IEQ
Lower IEQ means lower domain cryptographic exposure under GWK methodology. Full 0–100 scale.
Source: GWK · IEQ V2 · October 2026. Independent domain analysis of hubspot.com and freshworks.com; shared sector horizon parameter. Methodology
Under GWK methodology, hubspot.com has lower measured cryptographic exposure than freshworks.com. The independent domain-score comparison adds that dimension to the companies' disclosed financial indicators and security credentials.
Security assurance and cryptographic exposure answer different questions. A business comparison needs both.
The economic bridge: migration and residual losses
When a sufficiently capable quantum computer can break RSA using Shor's algorithm, an investor's question will extend beyond spending on conventional controls. It will include the work still needed to protect cryptographic dependencies and the economic value exposed during that work.
GWK's Quantum Exposure-Adjusted Financial Risk Model, or QE-FRM, expresses economic exposure as expected migration costs plus expected residual losses, conditioned on IEQ and organizational characteristics over a defined horizon. The cost ledger keeps the two components disjoint. Their expected values can be added even when the components are dependent.
Migration
Remaining engineering, integration, supplier coordination and testing expenditure.
Residual losses
Net financial consequences of cryptographic events affecting the exposure that remains during the transition.
Up to US$12.98 million between hypothetical scenarios
Scenario A uses IEQ 35.7; scenario B uses IEQ 2.2. Both are hypothetical and share the same revenue base and migration expenditure. The scale reference is US$3.682 billion, the midpoint of HubSpot's public 2026 revenue guidance. This figure supplies the calculation's revenue scale.
Under the specified direct-proportionality loss function, scenario A has a total burden of US$29.09 million and scenario B of US$16.11 million, in present value over three years. The US$12.98 million difference comes entirely from the expected residual-loss component of the scenarios.
Upper bound of the difference between hypothetical scenarios A and B
US$ 12.98 million
Present value · IEQ 35.7 versus 2.2 · same revenue base · direct-proportionality loss function (a = 1) · assumed 10% event probability and 5% net loss · range US$0 to 12.98 million, US$10.40 million at the midpoint.
| Component | Scenario A · IEQ 35.7 | Scenario B · IEQ 2.2 |
|---|---|---|
| Migration | 15.26 | 15.26 |
| Expected residual loss | 13.83 | 0.85 |
| Total | 29.09 | 16.11 |
The scenario difference varies with the loss function.
Hypothetical scenarios · same revenue base
Present-value difference between hypothetical scenarios at IEQ 2.2 and 35.7, for each specified score-to-loss relationship.
Calculation: GWK. Score-to-loss elasticity varies across a = 0, 0.25, 0.5 and 1; other scenario parameters remain fixed. Formula and inputs are specified below.
With no score-to-loss relationship, the monetary difference is zero. It rises to US$6.94 million at elasticity 0.25, US$10.40 million at 0.5 and US$12.98 million under direct proportionality. The sensitivity analysis quantifies how the chosen economic relationship translates the observed exposure distinction into the transition's economic impact.
A new dimension for comparing businesses
The independent GWK analysis identifies distinct cryptographic exposures in two real domains. The separate economic calculation uses those IEQ levels as inputs to hypothetical scenarios. Together, these two layers show how to incorporate measured domain exposure and an explicit estimate of the transition's economic impact into business analysis.
For an investment committee, that analysis leads to three questions:
- Which observed domain has lower cryptographic exposure under GWK methodology?
- What migration expenditure and residual losses follow under the economic scenarios being evaluated?
- How is the transition's economic impact incorporated into the business valuation?
IEQ distinguishes exposure. Explicit economic scenarios quantify the transition's economic impact.
This is GWK's contribution to organizing the market: a quantitative domain-exposure measure, an economic framework for migration and residual losses, and reproducible scenarios connecting the two. The measured IEQs are 2.2 and 35.7. In the separate calculation, hypothetical scenarios using those levels differ by up to US$12.98 million in present value under the stated assumptions, or about US$3.5 million per US$1 billion of revenue.
Method and sources
Inputs and calculation specification
Technical evidence: GWK · IEQ V2 · October 2026. Independent analysis under GWK methodology of hubspot.com (2.2) and freshworks.com (35.7), with the same sector horizon. Financial context: Q2 2026 issuer results and trust-center disclosures.
Monetary scenario: annual revenue base R = US$3.682 billion; horizon T = 3 years; annual discount rate r = 10%. Migration expenditure is 0.5% of R, paid in three equal year-end installments. At reference IEQ 35.7, the assumed cumulative event probability is 10%, and conditional net loss is 5% of R. Residual losses exclude spending counted in migration and are placed at the end of year three.
The equations below define expected residual loss and the present values of migration and total burden. Here p = 0.10, s = 0.05 and r = 0.10. Sensitivity uses a = 0, 0.25, 0.5 and 1, with a = 0 defined as no score-to-loss relationship. These elasticities are scenario inputs. Revenue scale and migration expenditure remain fixed.
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