Quantum-Si Inc
NASDAQ:QSI
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Quantum-Si Inc
Cash Taxes Paid
Quantum-Si Inc
Cash Taxes Paid Peer Comparison
Competitors Analysis
Latest Figures & CAGR of Competitors
| Company | Cash Taxes Paid | CAGR 3Y | CAGR 5Y | CAGR 10Y | ||
|---|---|---|---|---|---|---|
|
Q
|
Quantum-Si Inc
NASDAQ:QSI
|
Cash Taxes Paid
N/A
|
CAGR 3-Years
N/A
|
CAGR 5-Years
N/A
|
CAGR 10-Years
N/A
|
|
|
Thermo Fisher Scientific Inc
NYSE:TMO
|
Cash Taxes Paid
N/A
|
CAGR 3-Years
N/A
|
CAGR 5-Years
N/A
|
CAGR 10-Years
N/A
|
|
|
Danaher Corp
NYSE:DHR
|
Cash Taxes Paid
$1.6B
|
CAGR 3-Years
0%
|
CAGR 5-Years
19%
|
CAGR 10-Years
11%
|
|
|
Mettler-Toledo International Inc
NYSE:MTD
|
Cash Taxes Paid
N/A
|
CAGR 3-Years
N/A
|
CAGR 5-Years
N/A
|
CAGR 10-Years
N/A
|
|
|
Agilent Technologies Inc
NYSE:A
|
Cash Taxes Paid
$340m
|
CAGR 3-Years
19%
|
CAGR 5-Years
22%
|
CAGR 10-Years
N/A
|
|
|
IQVIA Holdings Inc
NYSE:IQV
|
Cash Taxes Paid
N/A
|
CAGR 3-Years
N/A
|
CAGR 5-Years
N/A
|
CAGR 10-Years
N/A
|
|
Quantum-Si Inc
Glance View
Quantum-Si, Inc. develops a protein sequencing platform of proteomics. The company is headquartered in Guilford, Connecticut and currently employs 153 full-time employees. The company went IPO on 2020-09-04. The firm has designed and developed a hardware and software solution to provide a full end-to-end solution. The firm has developed a single molecule detection platform to enable Next Generation Protein Sequencing (NGPS), the ability to sequence proteins. The Company’s platform is comprised of the Carbon automated sample preparation instrument; the Platinum NGPS instrument’ the Quantum-Si Cloud software service, and reagent kits and chips for use with its instruments. Its Carbon instrument is an automated sample preparation instrument that is designed for use in both protein and deoxyribonucleic acid (DNA) applications. Its Platinum is designed to make the power of single-molecule detection and NGPS broadly accessible. Its Quantum-Si Cloud platform is designed to integrate a cloud-based solution into the instrument to stream data in real-time to the cloud, where analytical workflows can then interpret the data.
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