Seeing Machines (LSE:SEE) Mohanram G-Score: 4 (As of Dec. 2025) — 33% Above Median


What is Seeing Machines Mohanram G-Score?

Seeing Machines LSE:SEE Mohanram G-Score is 4 as of Dec. 2025, which is 33% above its 10-year median of 3.00. The stock has 6 warning signs investors should review.

Mohanram G-Score is a financial indicator developed by professor Partha Mohanram to help investors find the best investment opportunities in the growth stocks. Companies have higher G-score tends to generate higher return. According to his study, the best growth stocks that have a G-Score greater than 6 tend to beat the market, while those with a G-Score lower than 1 tend to have negative absolute returns.

Thus, the zones of discrimination were as such:

Good or high score = 6, 7, 8
Bad or low score = 0, 1

Seeing Machines has an G-score of 4.

The historical rank and industry rank for Seeing Machines's Mohanram G-Score or its related term are showing as below:

LSE:SEE' s Mohanram G-Score Range Over the Past 10 Years
Min: 2   Med: 3   Max: 4
Current: 4

During the past 13 years, the highest Piotroski G-score of Seeing Machines was 4. The lowest was 2. And the median was 3.

Seeing Machines  (LSE:SEE) Mohanram G-Score Explanation

Partha Mohanram is the John H. Watson Chair in Value Investing at Rotman and the Acting Vice-Dean of Research Strategy and Resources.

In 2000, he wrote a research paper called "Separating Winners from Losers Among Low Book-to-Market Stocks Using Financial Statement Analysis".

This paper tests whether a strategy based on financial statement analysis of low book-to-market (growth) stocks is successful in differentiating between winners and losers in terms of future stock performance. Based on the research, a strategy based on buying high G-score (6, 7 or 8) firms and shorting low G-score (0 or 1) firms consistently earns significant excess returns. Further, the results do not support a risk based explanation for the book-to-market effect as the strategy returns positive returns in all years, and firms that ex-ante appear less risky have better future returns.

To conclude, one can use a modified fundamental analysis strategy (G-score) to identify mispricing and earn substantial abnormal returns.


Seeing Machines Mohanram G-Score Related Terms


Seeing Machines Mohanram G-Score Historical Data

* Premium members only.

The historical data trend for Seeing Machines's Mohanram G-Score can be seen below:

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

Seeing Machines Mohanram G-Score Chart

Seeing Machines Annual Data
Trend Jun16 Jun17 Jun18 Jun19 Jun20 Jun21 Jun22 Jun23 Jun24 Jun25
Mohanram G-Score
Get a 7-Day Free Trial Premium Member Only Premium Member Only 2.00 3.00 2.00 4.00 4.00

Seeing Machines Semi-Annual Data
Jun16 Dec16 Jun17 Dec17 Jun18 Dec18 Jun19 Dec19 Jun20 Dec20 Jun21 Dec21 Jun22 Dec22 Jun23 Dec23 Jun24 Dec24 Jun25 Dec25
Mohanram G-Score Get a 7-Day Free Trial Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only N/A 4.00 N/A 4.00 N/A

LSE:SEE vs MSFT, ORCL, PLTR: Mohanram G-Score Comparison

For the Software - Infrastructure subindustry, Seeing Machines's Mohanram G-Score, along with its competitors' market caps and Mohanram G-Score data, can be viewed below:

* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.


Seeing Machines Mohanram G-Score vs Software Industry

For the Software industry and Technology sector, Seeing Machines's Mohanram G-Score distribution charts can be found below:

* The bar in red indicates where Seeing Machines's Mohanram G-Score falls into.



Seeing Machines Mohanram G-Score Calculation

The calculation of the Mohanram G-score consists of eight criteria. Assign one point for each criterion met, then add up all the points to get the G-Score.

Profitability

Question 1. Return on Assets (ROA)

ROA % is calculated as Net Income divided by its average Total Assets over a certain period of time. It measures how well a company uses its asset to generate earnings.

Score 1 if ROA > ROA Industry Median, 0 otherwise.

Question 2. Cash ROA

Cash ROA equals to Cash Flow from Operations divided by average Total Assets. It measures how well a company uses its asset to generate cash.

Score 1 if Cash ROA > Cash ROA Industry Median, 0 otherwise.

Question 3. CFO and Net Income

Score 1 if CFO > Net Income, 0 otherwise.

Earnings Predictability

Question 4. Earnings Variability

Earnings Variability is measured as the variance of a firm's ROA in the past five years.

Score 1 if Earnings Variability < Earnings Variability Industry Median, 0 otherwise.

Question 5. Sales Growth Variability

Sales Growth Variability is measured as the 5-year variance in sales growth.

Score 1 if Sales Growth Variability < Sales Growth Variability Industry Median, 0 otherwise.

Accounting Conservatism

Question 6. Research & Development Intensity

Research & Development Intensity is calcualted by Research & Development divided by the beginning Total Assets.

Score 1 if Research & Development Intensity > Research & Development Intensity Industry Median, 0 otherwise.

Question 7. CAPEX Intensity

CAPEX Intensity is calcualted by Capital Expenditure divided by the beginning Total Assets.

Score 1 if CAPEX Intensity > CAPEX Intensity Industry Median, 0 otherwise.

Question 8. Advertising Expenditure Intensity

Advertising Expenditure Intensity is calcualted by Advertising Expenditure divided by the beginning Total Assets. Note that Advertising Expenditure is not reported as a seperate line item for many companies, thus Selling, General, & Admin. Expense is used in this calculation.

Score 1 if Advertising Expenditure Intensity > Advertising Expenditure Intensity Industry Median, 0 otherwise.

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

* Note that all the Industry Median used for comparison in his original research, are substituted with Sector Median due to the limitation of data within certain countries.

Good or high score = 6, 7, 8
Bad or low score = 0, 1

Seeing Machines has an G-score of 4.

Frequently Asked Questions Learn more about Mohanram G-Score →
What does a Mohanram G-Score of 4 mean?
Seeing Machines (LSE:SEE) has a Mohanram G-Score of 4 as of Dec. 2025. G-Score is a financial indicator developed by professor Partha Mohanram to help investors find the best investment opportunities in the growth stocks. View historical data on Seeing Machines and its competitors. This is 33% above median its historical median of 3.00. Over the past decade, Seeing Machines' Mohanram G-Score has ranged from 2.00 to 4.00.
Is Seeing Machines' Mohanram G-Score too high?
Seeing Machines' current Mohanram G-Score of 4 is 33% above median its 10-year median of 3.00. Over the past 10 years, this metric has ranged from a low of 2.00 to a high of 4.00.
How does Seeing Machines' Mohanram G-Score compare to MSFT and ORCL?
Seeing Machines' Mohanram G-Score of 4 can be compared against companies in the Software industry. Historically, Seeing Machines' own Mohanram G-Score has ranged from 2.00 to 4.00 over the past decade. See the competitive comparison table and distribution chart on this page for a detailed peer-by-peer breakdown.
What is a good Mohanram G-Score for a Software company?
A good Mohanram G-Score depends on the Software industry context. However, Mohanram G-Score should not be evaluated in isolation — investors should consider it alongside profitability, growth, and financial strength metrics. Use the industry distribution chart on this page to see where any company falls relative to its peers.
What does a high Mohanram G-Score mean?
A high Mohanram G-Score can signal that a stock is expensive relative to its fundamentals. G-Score is a financial indicator developed by professor Partha Mohanram to help investors find the best investment opportunities in the growth stocks. View historical data on Seeing Machines and its competitors. Seeing Machines's current Mohanram G-Score is 4, which is 33% above median its own 10-year median of 3.00. However, context matters — high-growth companies often justify higher valuations. Always evaluate alongside other metrics like GF Score™ and GF Value™.
Is Seeing Machines stock overvalued right now?
Based on GuruFocus' analysis, Seeing Machines (LSE:SEE) is currently considered Possible Value Trap. The stock's GF Value™ is £0.07, compared to a current price of £0.04 — trading 37.1% below its estimated fair value. The current Mohanram G-Score is 4, which is 33% above median its 10-year median of 3.00. Investors should evaluate multiple metrics — including profitability, growth, and financial strength — before making a decision.
How is Mohanram G-Score calculated?
Mohanram G-Score is calculated from a company's financial statements. For Seeing Machines (LSE:SEE), the current Mohanram G-Score is 4 as of Dec. 2025. GuruFocus calculates this using data sourced from SEC filings and annual reports. See the calculation section and 30-year financial data on this page for the full breakdown.

Seeing Machines Business Description

Other Exchanges SEEMF:USASEEl:UKM2Z:Germany
Address 80 Mildura Street, Fyshwick, Canberra, ACT, AUS, 2609
Seeing Machines Ltd develops, sells, and licenses products and technology to detect and manage driver fatigue and distraction, partnering for product development, manufacturing, and sales in key markets. It operates two segments: the OEM segment, covering automotive and aviation business units that generate license-based royalties and non-recurring engineering services via Tier 1 customers; and the Aftermarket segment, comprising Fleet and Off-Road units that retrofit technology into commercial vehicles through direct and indirect customers. The Company operates in Australia, North America, Asia-Pacific (excluding Australia), Europe, and other regions, with the majority of revenue coming from Europe.