Matrice
Build, deploy, and monitor computer vision applications with image data and existing camera streams.
Matrice enterprise vision AI platform overview
About Matrice
Matrice is an enterprise vision AI platform that turns existing camera feeds and image datasets into deployed computer vision applications. Its workflow covers dataset versioning, splitting and cleaning, collaborative labeling, AutoML training, online testing, evaluation, deployment, and monitoring. Teams can keep existing cameras, run multiple AI applications on one stream, and choose platform cloud, customer cloud, reserved compute, or on-premise operation. The Free plan includes 50 monthly credits and five seats; Academia includes 100 credits. Team provides 500 credits, ten seats, assisted annotation, edge optimization, drift monitoring, traffic monitoring, and compute reservation for $299 per month. Because storage, training, evaluation, deployment, API use, and monitoring consume credits differently, buyers should estimate a representative workload before selecting a plan.
Best for
Best use cases
Prepare and label image datasets before training a vision model
Train, test, evaluate, deploy, and monitor models in one workflow
Run vision applications on existing camera streams across operational sites
Compare before choosing
Free includes 50 credits and 5 seats, while Academia includes 100 credits and the same seat cap
Team costs $299 per month and adds 500 credits, 10 seats, monitoring, and compute reservation
Enterprise uses custom pricing and adds on-premise compute, predictive analytics, and dedicated support
Features
Safety and compliance monitoring
Use existing camera feeds to detect PPE compliance, perimeter events, and other operational safety conditions. This suits industrial sites that want automated checks without replacing their camera hardware.
Retail and facility analytics
Analyze queues, footfall, patient flow, resource use, and staff operations from camera streams. Operators can use the results to investigate congestion and adjust staffing or facility processes.
Model development and deployment
Prepare image datasets, label data, train and evaluate models, then deploy them and monitor drift and live traffic. The shared workflow reduces transfers between separate data, model, and operations tools.
Pros
- A $0 Free plan includes 50 monthly credits and up to five seats, lowering the cost of initial evaluation.
- The workflow spans dataset preparation, annotation, training, testing, deployment, and monitoring, reducing handoffs between separate tools.
- Enterprise supports on-premise compute, which gives organizations an option to keep video workloads inside their own infrastructure.
Cons
- Training, evaluation, deployment, storage, and monitoring consume credits at different rates, so monthly cost can be difficult to estimate without a workload model.
- The Team plan costs $299 per month, which may be expensive for small groups that outgrow the free credit allowance.
- Several operational capabilities, including drift monitoring and compute reservation, require Team, while on-premise compute requires Enterprise.
Pricing Plans
Free
- 50 monthly credits
- Additional credits at $1.00 each
- Up to 5 user seats
- 10,000 images per account
- Dataset versioning, cleaning, collaborative labeling, AutoML, online testing and evaluation, and Python SDK support
Academia
- 100 monthly credits
- Additional credits at $1.00 each
- Up to 5 user seats
- 100,000 images per account
- Everything in Free, plus dataset augmentation
Team
- 500 monthly credits
- Additional credits at $0.50 each
- Up to 10 user seats
- Unlimited images
- ML-assisted annotation, edge optimization, drift and traffic monitoring, and compute reservation
Enterprise
- Custom monthly credits and user seats
- Additional credits at $0.50 each
- Unlimited images
- Everything in Team, plus dedicated expert support, on-premise compute, and predictive analytics
* Pricing information is for reference only. Please refer to the latest announcement on Matrice's official website.