Valuation: NetraMark Holdings Inc.

Market Cap 61.51M 44.51M 38.18M 35.65M 32.71M 4.25B 62.52M 421M 165M 2.13B 167M 163M 7.05B P/E 2026 *
-
P/E 2027 * -
Enterprise Value 61.51M 44.51M 38.18M 35.65M 32.71M 4.25B 62.52M 421M 165M 2.13B 167M 163M 7.05B EV / Sales 2026 *
153x
EV / Sales 2027 * -
Free-Float
91.14%
Yield 2026 *
-
Yield 2027 * -
1 day+4.06%
1 week+2.54%
Current month-11.78%
1 month-11.35%
3 months-28.21%
6 months-32.96%
Current year-36.43%
1 week 0.49
Extreme 0.4858
0.51
1 month 0.47
Extreme 0.4702
0.6
Current year 0.4
Extreme 0.40134
0.89
1 year 0.4
Extreme 0.40134
1.26
3 years 0.11
Extreme 0.114
1.26
5 years 0.1
Extreme 0.1045
1.61
10 years 0.1
Extreme 0.1045
1.61
Manager TitleAgeSince
Chief Executive Officer - 2022-02-16
President - 2022-07-03
Director of Finance/CFO 57 2022-07-17
Director TitleAgeSince
Chairman 40 2025-06-08
Director/Board Member - -
Director/Board Member - 2022-06-15
Change 5-day change 1-year change 3-year change Capi.($)
+4.06%+2.54% - - 44.28M
+0.38%-1.66%-5.00%+50.45% 3,576B
+1.80%+2.34%+10.96%+1,107.21% 412B
+0.08%-1.72%-8.45%+41.15% 87.17B
-4.79%-2.81%+81.51%+147.26% 88.33B
+0.01%-1.77%-33.90%-7.20% 77.44B
+2.68%-6.71%-33.32%+209.08% 71.21B
-1.64%-1.93%+4.36%+70.77% 45.32B
+7.53%+12.50%+5.07%-5.16% 41.26B
-4.11%-9.68%+115.57%+267.82% 35.64B
Average +0.56%-3.33%+15.20%+209.04% 492.77B
Weighted average by Cap. +0.46%-4.07%-1.66%+153.40%

Financials

2026 *2027 *
Net sales 401K 290K 249K 232K 213K 27.73M 408K 2.74M 1.07M 13.91M 1.09M 1.07M 45.98M -
Net income - -
Net Debt - -
Logo NetraMark Holdings Inc.
NetraMark Holdings Inc. is a Canada-based company, which is focused on the development of Generative Artificial Intelligence (Gen AI)/Machine Learning (ML) solutions targeted at the pharmaceutical industry. The Company’s product offering uses a novel topology-based algorithm that has the ability to parse patient data sets into subsets of people that are strongly related according to several variables simultaneously. This allows the Company to use a variety of ML methods, depending on the character and size of the data, to transform the data into powerfully intelligent data that activates traditional AI/ML methods. The result is that it can work with smaller datasets and accurately segment diseases into different types, as well as accurately classify patients for sensitivity to drugs and/or efficacy of treatment. The typical molecular data used is RNASeq, microarray, single nucleotide polymorphism (SNP) and methylation.
Employees
-
Date Price Change Volume
26-08-14 $0.5055 +4.06% 500
26-08-13 $0.4858 +3.32% 500
26-08-12 $0.4702 -4.62% 7,050

Quarterly revenue - Rate of surprise