COMPUTER VISION WITH DORI



Accelerate Solution Development

Building computer vision applications and systems requires a unique combination of expertise, tools, and infrastructure. Dori provides a complete end-to-end platform that enables robust dataset/ML model creation, streamlines development, and accelerates time-to-market.







RAPID LOW-CODE DEVELOPMENT


Made for application developers; intuitive for data scientists. Unify development efforts across multiple stakeholders.


FULL STACK PLATFORM


Fully integrated workflow to build, train, deploy, and monitor AI in your real-world systems


DATASET & ML MODEL CREATION


Robust tools to create/enrich datasets and build custom ML models across various use cases.

APPLICATION BUILDER

Dori provides enterprises with a customizable dashboard visual interface to rapidly create computer vision applications. The Dori Vision platform enables a robust suite of tools to quickly ensemble multiple data connectors, ML models, and application plugins to satisfy any computer vision use case.


  • Connect any camera, image, video, or data stream.
  • Build applications to detect objects, people, docs, etc.
  • Launch scalable solutions & receive actionable insights.



DEEP LEARNING ENGINE

The end-to-end integrated Deep Learning Engine accelerates the development and deployment of ML models in any framework. The platform natively supports data connectors to various sources (cameras, streaming interfaces, cloud storage, etc), a proprietary visual annotation tool, and a seamless dashboard workflow to train, optimize, and benchmark ML models.


  • Robust selection of pretrained models and architectures.
  • Customize models for your data and use case.
  • Evaluate and upgrade models with ease.



DEPLOYMENT MONITOR

Dori provides seamless support and scalable optimized deployment across edge and cloud. The platform enables monitoring of models and runtime data for any anomalies or model/data drifts throughout the inference lifecycle.


  • Scalable workflow for device/instance management.
  • Model explainability and bias analysis.
  • Monitor system utilization and performance.