Nightingale HQ

We founded Nightingale HQ because we believe data science is an important capability that even small and medium sized businesses need to adopt. The biggest problem we’ve seen though is that the implementation of data science is a lot more difficult than many appreciate.

Our aim is to provide an intuitive platform that can help businesses learn about data science in a buzzword free way and manage the adoption of data science in a painless way.

Florence Nightingale

Almost everyone has heard of the Lady with the Lamp. Florence worked as a nurse during the Crimea War and her local intervention made the difference in hundreds, possibly thousands of lives. Her real legacy though was her data science work that revolutionised medical care and has saved countless lives since then!

Florence performed comprehensive studies into sanitation and medical care. The key to the success of her work was ultimately in her ability to communicate her findings outside of her field.

Making a difference and being able to translate complex statistical work into something that provides value is what we would most like to achieve. Thus we put our aspiration into our name!

Investment and support

We’re an early-stage startup currently part of the Accelerated Growth Programme and it’s accelerator. We’re currently bootstrapping ourselves during our MVP phase, but we are looking for investors who can support our aspiration to help businesses globally. If you’re interested in learning more, contact us at founders@nightingalehq.ai

Vital Information

• Nightingale HQ Ltd
• Registered in England and Wales: 11725529
• First Floor - 29 Gelliwastad Road, Pontypridd, United Kingdom, CF37 2BN

How we make our money

Connecting you to the right partner for your needs means that the partner earns money and, best for them, they earn it helping those who are they best suited to help. We take a commission for these successful introductions.

Meet The Team

Our founders are experts in their respective fields, data science and software engineering,who understand what it takes to integrate data science into organisations.