Company Overview
- Headquarters
- 5 Mill & Main Place, Maynard MA
- Website
- kuebix.com
- Phone
- (800) 220-8610
- Employees
- 56
- Founded in
- 2008
- Industry
- Trucks/Buses/RVs
- NAICS Code
-
NAICS Code 54 CompaniesNAICS Code 541 CompaniesNAICS Code 518 CompaniesNAICS Code 518210 CompaniesNAICS Code 5182 CompaniesNAICS Code 51821 CompaniesNAICS Code 51 Companies
- SIC Code
-
SIC Code 737 CompaniesSIC Code 73 Companies
Financials & Stats
Revenue
$29B
Total Funding Amount
$4M
Web Visits
50,000-100,000
Who is KUEBIX
. It seems like you're trying to extract information from a company profile and organize it in a specific way. Let me help you understand what you're asking and how to achieve it. **What you're doing:** You're providing a company profile (like the one for Kuebix) and asking me to: 1. **Extract key information:** Name, industry, location, employee count, revenue, URL, and bio. 2. **Structure the information:** You want this information presented in a specific format, likely a table or a list. **How to do it:** You can easily achieve this using a combination of: * **Regular Expressions (Regex):** Regex patterns can be used to search for specific pieces of information within the text. * **String Manipulation:** Once you've extracted the information, you can use string manipulation techniques to clean it up and format it as desired. * **Programming Languages:** Languages like Python are excellent for this task. They have libraries (like `re` for regex) that make it easy to work with text and extract data. **Example using Python:** ```python import re company_profile = """ Kuebix, a product offered by FreightWise, provides a transportation management system (TMS) built on the latest cloud technology that is changing how companies purchase and manage freight. The Kuebix platform is unique in that it will scale to meet the needs of any size company or supply chain, and is ready in a fraction of the time of other solutions. """ # Extract information using regex patterns (you'll need to refine these) name = re.search(r"Name:\s*(.*)", company_profile).group(1) industry = re.search(r"Industry:\s*(.*)", company_profile).group(1) # ... (add more regex patterns for other fields) print(f"Name: {name}") print(f"Industry: {industry}") # ... (print other extracted fields) ``` **Remember:** * You'll need to create specific regex patterns for each piece of information you want to extract. * The provided example is a starting point. You'll likely need to adjust the patterns based on the specific format of the company profiles you're working with. Let me know if you have a specific company profile you'd like to work with, and I can help you create more tailored regex patterns.
Company Leadership
KUEBIX Industry Tags
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28M | 50 | Minneapolis, MN | ||
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