Contact Us

Connect with us to schedule a consultation

We're here to help you transform your statistical and data science needs. Our team of experts is ready to provide personalized solutions for your organization.

How to Reach Us

Phone

301-850-1023

Fax

1-866-224-7935

Address

137 National Plaza,
National Harbor, MD, 20745

Business Hours

Monday to Friday: 9AM - 5PM EST

Need Immediate Assistance?

Our support team is available during business hours for urgent inquiries.

NNIPA Headquarters

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FAQ

Frequently Asked Questions

Find answers to common questions about our services and solutions

Q:What services does NNIPA offer?

NNIPA provides a comprehensive suite of data integration, statistical analysis, and AI-powered solutions specifically designed for population data science and research institutions.

Q:How can I schedule a demonstration?

You can schedule a demonstration by filling out our contact form, calling our office at 301-850-1023, or clicking on the 'Schedule a Meeting' button at the top of this page.

Q:Do you offer customized solutions?

Yes, we specialize in creating tailored solutions that meet the specific needs of your organization's data challenges and goals. Our team works closely with you to understand your requirements.

Q:What support options are available?

We offer comprehensive support packages including training, ongoing maintenance, and dedicated technical assistance for all our solutions. Support tiers are available to match your organization's needs.

Q:Can NNIPA integrate with our existing systems?

Yes, our solutions are designed with interoperability in mind. We can integrate with most existing statistical software, data management systems, and research platforms.

Q:What industries do you serve?

We primarily serve government agencies, research institutions, healthcare organizations, and educational institutions that work with population data and statistics.

Ready to Transform Your Data Experience?

Join the community of statistical professionals using NNIPA to revolutionize their approach to population data science.