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Dataloop SDK

End-to-end automation of your computer vision pipelines

Dataloop SDK

SDK highlights

At Dataloop, we make sure to “eat own own dog food”, as our entire platform is built on top of our SDK that runs via our Rest APIs. These give you direct access to our production environment with your code, so you can easily perform actions like:

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Integrate your own ML models to automatically annotate raw data, thus turning the manual labeling process into a simple auditing task - the labelers only fix annotations rather than label from scratch

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Pre processing

Prepare your data for more efficient workflows, with automatic functions such as cutting video files into individual frames, selecting only high variance items for manual annotations, enhancing image and video quality and more

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Make more sense of your annotated datasets both before and after training. Run auto-clustering functions to identify gaps in the dataset, optimize data variance, and use quality analyzers to measure model confidence rates

SDK applications for production pipelines

Custom Plugins

Create your own plugins in Python with our SDK, including built-in triggers for running functions and auto-scaling them. Bootstrap and manage your plugins using our interactive CLI with auto-completion of commands and parameters

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Build Custom Pipeline Plugins
Build Custom Pipelines

Custom Pipelines

Assemble event-driven automation pipelines for running pre and post processing functions, integrate models into annotation workflows and training iterations, deploy models in production and introduce a human-in-the-loop for edge-case validation

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Serverless Data Applications

Build, operate and deploy pipelines at scale, utilizing our Kubernetes-powered environment for running containerized models during research, training and production – all compute infrastructure can be handled by us and supported for unlimited auto-scaling

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Storage management

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An end-to-end cloud-based annotation platform, with embedded tools and automations for producing high-quality datasets more efficiently.

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Build custom automation pipelines within our serverless environment, to reach production faster and scale indefinitely.

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Enterprise-grade data engine

Ensuring highest data standards that serve your entire data organization, allowing cross-functional collaboration while keeping your data access internal

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Custom authentication and role permission enforcement. Using advanced Kubernetes-powered infrastructure for on-premises or private storage deployments

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Full encryption to keep your data constantly safe, compliant with military-grade security standards and certified by comprehensive system audits

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High performance for large volumes of data with 99.9% uptime SLA, providing auto-scaling infrastructure that supports your ever-growing data operations

Yeshiaya Odysight
Yishaia Zabary
Senior Data Scientist
david lempert
David Lempert
Head of R&D
Ido ariav
Ido Ariav
Deep Learning Lead