Training Data

Deploy high quality AI models
with robust training data

Quickly develop data-sets, improve algorithm accuracy and structure your data effectively.

Precise focus

Ask exact questions to train within the exact areas you’re looking for

Robust process paths

Our thoughtfully designed process paths provide high quality training

Flexible scaling

We can dial your training efforts up and down depending on your need

Blended human input

Ensure the highest levels of accuracy with vetted worker pools

There’s no AI without
data to train models

Every problem statement you target with AI or every model you create needs new data to train it. Precision is essential, you need to be focused on exact questions, and quality is paramount, every bad or inaccurate decision is feeding errors into the foundations of your model.

Using data targeted at your exact output goals, we build robust process paths to create accurate labels. Combining the highest quality human input with machine learning, our training is application specific and precisely focused on your requirements.

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

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.