Where AI meets
the real world.
Bring ambitious, sensor-driven machine-learning products into production through integrated data-collection and testing.
Our Customers and Partners
Production is where ML goes to die. Successful real-world ML requires a closed-loop.
Today, AI too often is built in isolation. Teams build models, deploy them to the edge but have little insight into how they perform in the real world and if they work for their users in every edge-case.
An E2E platform for Data Collection, Model Development, and Testing.
All your data, in one place.
Manage all your data in one place from day one. From manually collected data to field-data, FieldDay means no more tedious looking through S3-buckets.
Collaborative timeline interface.
FieldDay lets you look at collected events on a timeline alongside annotations and analytics from the field making it simple to understand what is going on.
FieldDay lets you load any model and run it over field data, enabling powerful analysis and automatic detection of false-positives.
Run on your hardware.
Integrate into your existing hardware infrastructure. Start emitting FieldDay data events and you will start to see data show up in the dashboard.
Manage your device settings.
Manage device settings from the FieldDay dashboard, giving your modelling team control over the quality and consistency of the data being collected.
If your hardware is not ready yet we have assembled production-ready hardware in a neat little kit that you can start collecting data with today.
Ready-to-go Collection Tools
Real-time, interactive labelling
Annotating time-series data after the fact is hard. Our real-time annotation interface allows your collection team to annotate data while they collect.
Connects with your hardware
The FieldDay SDK on your hardware will automatically be available through our Collect Interface on Android or iOS.
Configurable + live metadata
Add custom metadata before starting a collection session. API-driven data like weather or location is updated automatically and continuously.
Frequently asked questions