DataChat

Data Chat

Computer Software, 1403 University Ave, Madison, Wisconsin, 53715, United States, 11-50 Employees

datachat.ai

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phone no Phone Number: 26********

Who is DATACHAT

DataChat is a no-code, generative AI platform that makes complex data analytics accessible to everyone. You no longer need to have a technical background or phd in mathematics to do data ...

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  • 1403 University Ave, Madison, Wisconsin, 53715, United States Headquarters: 1403 University Ave, Madison, Wisconsin, 53715, United States
  • 2017 Date Founded: 2017
  • 11-50 Employees: 11-50
  • dollar-icon Revenue: $1 Million to $5 Million
  • tech-icon Active Tech Stack: See technologies

industries-icon Industry: Computer Software

SIC SIC Code: 7372 | NAICS Code: 621111 | Show More

checked-icon Does something look wrong? Fix it. | View contact records from DATACHAT

DataChat Org Chart and Mapping

Employees

Similar Companies to DataChat

OtterTune

  • 11-50 11-50
  • 1 Million to 5 Million $ 1 Million to 5 Million

Sisense

  • 501-1000 501-1000
  • 250 Million to 500 Million $ 250 Million to 500 Million
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Frequently Asked Questions Regarding DataChat

Answer: DataChat's headquarters are located at 1403 University Ave, Madison, Wisconsin, 53715, United States

Answer: DataChat's phone number is 26********

Answer: DataChat's official website is https://datachat.ai

Answer: DataChat's revenue is $1 Million to $5 Million

Answer: DataChat's SIC: 7372

Answer: DataChat's NAICS: 621111

Answer: DataChat has 11-50 employees

Answer: DataChat is in Computer Software

Answer: DataChat top competitors include: OtterTune , Sisense

Answer: DataChat contact info: Phone number: 26******** Website: https://datachat.ai

Answer: DataChat is a no-code, generative AI platform that makes complex data analytics accessible to everyone. You no longer need to have a technical background or phd in mathematics to do data science. Load data from any cloud database or even an excel spreadsheet. Youre up and running in 10 minutes. You can run machine learning, run predictive models, do visualizations and ask questions of all your data in plain english. Whether its a seasoned data scientist, a spreadsheet-loving analyst, or a business user seeking plain-English answers, were breaking down complex customer data sets, and turning them into actionable insights.

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