Powering Advanced AI

Data labelling with confidence
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About Us

Our story

We are a venture-backed startup spun out of the University of Oxford, drawing on more than a decade of experience developed by the team behind the Zooniverse citizen science platform.

The Zooniverse uses novel machine learning in conjunction with a large, distributed crowd of participants to map the cosmos, fight diseases like TB and help in disaster relief. We build on these established tools, design practice and technical expertise to help an expanding list of clients, providing fast, flexible and powerful crowd-powered labelling and insight wherever it’s needed.


The team

  • Chris Lintott

    Chris is Professor of Astrophysics at the University of Oxford, working on machine learning in the service of serendipitous discovery, galaxy evolution and planet finding. He is co-presenter of the BBC’s long-running Sky at Night series.

  • Sophie Hackford

    Co-founder and Chair of 1715 Labs, Sophie is a futurist, who previously worked at WIRED Magazine, Singularity University at the NASA Research Park in Silicon Valley and Oxford University.

  • Daniel McMahon

    Dan comes to 1715 Labs as CEO from Amazon, having previously led teams and built business units across a wide range of settings, applications and sectors.

  • Roger Hutchings

    Before joining 1715 Labs as lead developer, Roger spent five years as a member of the Zooniverse citizen science team.

  • Colin Scott

    Colin joins 1715 Labs to drive development of our core product offering. He brings experience of launching and growing new businesses and product lines across a range of industries.

  • Your name here?

    Get in touch to discuss opportunities at 1715 Labs.


How can 1715 Labs help your business?

Performance improvement

Access to high-quality training data is the single biggest factor limiting AI performance. Ensure your AI reaches its full potential with 1715 Labs' confidence-driven approach.

Cost saving

Get your highly-trained data scientists focused on delivering business benefit and trust 1715 Labs to deliver high-quality labels and cost savings.


How does 1715 Labs work?

Any data type

Any data type

95%* of the world’s data is unstructured and unsuitable for onward analysis. Pictures, text, video and audio all require labelling before their value can be unlocked – we can tackle them all

Maximise the human element

Maximise the human element

Building on a world-class platform with 10 years of runtime, we take a deep psychological understanding of human input and maximise it with advanced technical levers & integrated statistical tools to deliver high-quality labelling with confidence

Any data type

Structured data that makes a difference

Control, flexibility and confidence (literally — thanks to our adapted Bayesian modelling) enables focused labelling strategies that solve problems



Computer vision

  • Image categorisation
    Image categorisation
  • Centre of mass dots
    Centre of mass dots
  • Bounding boxes
    Bounding boxes
  • Polygons
  • Lines
  • Semantic segmentation
    Semantic segmentation

Language processing

  • Text classification
    Text classification
  • Relationship identification
    Relationship identification
  • OCR transcription
    OCR transcription
  • Semantic segmentation
    Semantic segmentation
  • Sentiment recognition
    Sentiment recognition
  • Audio analysis
    Audio analysis
“The goal is to turn data into information and information into insight.”
Carly Fiorina
Former CEO, Hewlett Packard