AI is challenging to build. Our platform is designed to help your team focus on the most impactful tasks – to build and deploy performant, trustworthy, and reliable AI models faster.
Fix low quality samples
Use our quality score to identify errors that you can quickly triage and fix. Find anomalous samples, inconsistent labeling, wrong cropping and more. Collaborate and share the findings with your team.
Find data issues at scale
Expand and generalize existing issues at scale – go from a couple of incorrect sample to finding similar problems in the whole dataset. Identify risks for data leakage and remove duplicates from your datasets.
Gain model insights
Assess the quality of your data through model-guided data analysis. Find and generalize data issues, fix wrong or inconsistent labels, poor quality samples, or unbalanced data distributions.
Not all samples are created equal. Curate representative subsets, identify regions with degraded model performance and distribution shifts to improve the quality of your data. Query unlabelled datasets for relevant samples to include in your training or test dataset.
Benefits everyone on your team
All stakeholders in your organization including data analysts, domain experts, ML engineers can collaborate using a single source of truth in real-time to find and fix issues at scale.
What our customers say
Try LatticeFlow on your data
Small or large, with LatticeFlow be always one step away from finding the gaps in your data and how best to use it.
LatticeFlow offers both private cloud and on-premise deployment options to ensure you have complete control over your data and its privacy.
We do not offer a labeling service. However, our platform enables you to automatically identify data or labeling issues at scale.
Yes, you can plug in custom metadata associated both with images, as well as individual objects and segmentation.
Yes, we can run analysis on both static and dynamic data samples without having to start from scratch.