Ground truth

Make sure your AI is working from
accurate ground truth

Ensure strong foundations for your AI development with a human approach to setting the ground truth.

Create strong foundations

Ensure your AI is working from the most accurate possible truths

Scale human validation

Enable extremely high quality interpretations at scale

Handle subjective content

Ensure accuracy when dealing with difficult content

Gain confidence in outputs

Work from the highest quality inputs to be sure of your end results

AI is doomed to fail without
high quality base input

Training data and model validation both rely on knowing the ground truths. For example, what exactly does a banana look like? Getting this wrong means the foundations of your AI development will be compromised, so high quality input is essential to successful data teams.

Acquiring and gaining confidence in these inputs can be time consuming and painful, especially at scale. We mix human and machine analysis to enable high quality interpretations of difficult and subjective content, ensuring your models are set up to succeed.

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

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.

Labelled data from 1715 Labs helped our model improve robustness and consistency on real world noisy documents

Lorenzo Bongiovanni - Lead Machine Learning Scientist @ Amplyfi

1715 Labs' human-led approach unlocks hard to reach value in complex datasets

Derek Langley - Product Line Design Authority @ Thales
Trusted by data teams at
Nesta
Codemill

Contact us to
get your AI out of the lab

We'll guide you through the best solution and implementations to achieve your data goal and make the most of your artificial intelligence.