News analytics
Build custom, AI-powered news analytics applications that extract entities, events, and relationships from diverse news sources using Snorkel Flow.
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Deeply understand the impact of news
Snorkel Flow lets you build custom applications that analyze news and extract entities, events and relationships precisely. Go beyond brittle, off-the-shelf data feeds today–without the bottleneck of manual labeling.
High-accuracy models
Develop highly accurate models to decrease the potential of errors with guided iteration and built-in analysis tools.
With rising demand for affluent stay-at-home consumers, interactive fitness bike maker Peloton [ENTITY] agreed to buy [EVENT] Precor [ENTITY], a major provider of workout machines to gyms and hotels, for $420M [PRICE], its biggest purchase to date.
Faster, lower-cost extraction
Use programmatic labeling to train models that extract custom attributes in minutes instead of spending weeks or months on expensive hand-labeling.
Rapidly adaptable
Rapidly build apps that adapt to new attributes in a fraction of the time. Retrain models with ease to changing input data or business objectives.
Sentiment
Intent
Novelty
Topic
Temporal
Flexible integrations
Avoid vendor lock-in with easy integration of labeling, training, and analysis pipelines with diverse news sources or downstream applications using APIs or a Python SDK.
News
outlets
outlets
Social
media
media
Financial
news
Digital
feeds
Data-centric AI
Snorkel AI is leading the shift from model-centric
to data-centric AI development to make AI practical.
to data-centric AI development to make AI practical.
Accelerated
Save time and costs by replacing manual labeling with rapid, programmatic labeling.
Adaptable
Adapt to changing data or business goals by quickly changing code, not manually re-labeling entire datasets.
Collaborative
Incorporate subject matter experts' knowledge by collaborating around a common interface–the data needed to train models.
Accurate
Develop and deploy high-quality AI models via rapid, guided iteration on the part that matters–the training data.
Governable
Version and audit data like code, leading to more responsive and ethical deployments.
Private
Reduce risk and meet compliance by labeling programmatically and keeping data in-house, not shipping to external annotators.
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
Hand-labeled ML is hugely expensive, with usually no way to iterate, adapt, be privacy compliant, audit, or reuse.
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.
Let's connect
Speed time to value, reduce costs, and unlock more AI possibility with the Snorkel Flow platform.
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