AI For Insurance




From improving claims experience to fraud detection, Snorkel Flow provides insurance innovators with a data-centric platform to build custom AI applications powered by programmatic data labeling.




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Approach —




Data-Centric AI


Snorkel AI is leading the shift from model-centric to data-centric AI development to make AI practical.





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Accelerated


Save time and costs by replacing manual labeling with rapid, programmatic labeling.




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Accurate


Develop and deploy high-quality AI models via rapid, guided iteration on the part that matters–the training data.




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Adaptable


Adapt to changing data or business goals by quickly changing code, not manually re-labeling entire datasets.




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Governable


Version and audit data like code, leading to more responsive and ethical deployments.




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Collaborative


Incorporate subject matter experts' knowledge by collaborating around a common interface–the data needed to train models.




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Private


Reduce risk and meet compliance by labeling programmatically and keeping data in-house, not shipping to external annotators.











Use Cases —




AI Solutions For Insurance




AI applications built using Snorkel Flow can boost revenues through increased personalization for customers and employees, and lower costs through efficiencies generated by higher automation, reduced errors rates, and better resource utilization.




INSURANCE






Why Snorkel Flow —


A Radically New Approach to AI



Conventional AI approaches rely on generic third-party models, or brittle rule-based systems, or armies of human labelers. With Snorkel Flow, programmatically labeling unlocks a new workflow that accelerates AI app development.

With Snorkel Flow

  • Customize state-of-the-art models by training with your data & adapt to changing data or goals with a few lines of code.
  • Leverage cutting-edge ML to go beyond simple rules and retain the flexibility to audit and adapt.
  • Label thousands of data points programmatically in hours while keeping your data in-house and private.

With Conventional Approaches

  • Pre-trained vendor models often don’t work on your data, no way to customize, adapt, or audit.
  • Rules-based approaches often don’t perform well on complex data or adapt easily to data or goal changes.
  • Hand-labeled ML is hugely expensive, with usually no way to iterate, adapt, be privacy compliant, audit, or reuse.






Platform —



Snorkel Flow



The only AI platform that lets you label data programmatically, train models efficiently, improve performance iteratively, and deploy applications rapidly.




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01


Label & Build
Label and build training data programmatically in hours without months of hand-labeling
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02


Integrate & Manage
Automatically clean, integrate, and manage programmatic training data from all sources
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03


Train & Deploy
Train and deploy state-of-the-art machine learning models in-platform or via Python SDK
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04


Analyze & Monitor
Analyze and monitor model performance to rapidly identify and correct error modes in the data