Increase your control to
maximise advertising impact
Let our machine learning tools interpret subjective content at pace to ensure your target audience sees your content and maximise impact.
Human powered machine
Ensure a human-centric approach to subjective content decisions
Highly configurable
Surgical tools crafted around your exact needs
Protect against bad content
Monitor sentiment to avoid associations harmful to your brand
Maxmise your impact
Quickly find the best locations and returns on your advertising spend
Target effectively to
reinforce your brand
Automated advertising risks missing your target audience or, even worse, creating associations with content that can erode consumer perception of a brand. It's a constant battle to target effectively and at good value.
1715 Labs combines machine learning and human-centric analysis to make subjective decisions about content and locations that are positive for your brand and deliver great return on investment for your adverts.
One solution,
all your data types
Image detection
Detect objects and add context to analyse imagery
Shape recognition
Detect and categorise shapes and patterns in imagery
Video enhancement
Categorise, label and annotate video in real time
Boundary & route analysis
Understand and map out boundaries and routes
Powerful
language processing
Text
classification
Relationship
identification
OCR
transcription
Semantic
segmentation
Sentiment
recognition
Audio
analysis
Build your models with data training
Move past the pain of manual labelling by harnessing our distributed crowd, supported by more than 10 years' experience of running the world's largest citizen science platform.
Precise, custom focus
Robust process paths
Flexible, infinite scaling
Blended human input
dataset_name | type | analysis | accuracy |
---|---|---|---|
cx_calls | audio | analysis | |
store_cctv | video | categorisation | |
territories | image | bounding | |
uk_roads | image | route | |
interview | audio | transcription | |
checkout | video | annotation |
Model output validation at scale
Test and improve your data models with the highest quality human validation at scale. We help you monitor your deployed models at a greater speed and lower cost than other options.
Assess model suitability
Increase performance
Understand issues
Reduce assumptions
data_point | returned | answer | result |
---|---|---|---|
a_0042 | cube | cube | true |
a_0043 | triangle | polygon | false |
a_0044 | circle | circle | true |
a_0045 | polygon | triangle | false |
a_0046 | polygon | polygon | true |
a_0047 | triangle | triangle | true |
Understand the ground truth
Gather data from direct observation and quickly synthesize it to gain powerful insight.
Create strong foundations
Scale human validation
Handle subjective content
Gain confidence in outputs
id | type | coordinates | elevation |
---|---|---|---|
r_029 | river | 53.273,-7.778 | 32m |
m_032 | mountain | 59.439,9.394 | 858m |
f_067 | forest | -4.394,-84.039 | 93m |
f_068 | forest | 4.733,85.494 | 12m |
l_058 | lake | 84.958,-23.494 | 830m |
m_033 | mountain | -31.049,41.486 | 1284m |
Scale your labelling with no compromise on quality
A core challenge of data labelling is scaling your team. While small pools of workers can’t handle large datasets and increase the risk of individual error, large pools are hard to manage and likely to be less focused or knowledgable.
We have a ten year track record of using existing pools to take the weight of crowd management off your shoulders of world class companies. Participant input is statistically weighted based on their track record to combining the results of many workers for any given task and ensure the highest quality results.
Focus on unique problems with high level configuration
We provide well-tested solutions that can be rapidly implemented for more straight forward tasks, helping you focus on the more important and high impact work.
For more difficult tasks, unknown problems or new areas of research, our flexible internal toolkit and extensive experience in crowd labelling allows us to design and deploy workflows which focus crowd effort onto your specific problem. No more generic ‘place a bounding box’ results.