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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.
Use cases
AI solutions for telecom
AI applications built using Snorkel Flow make the most of data resources by integrating them with cutting-edge models and expertise. Automate manual, legacy labeling processes, and reserve expensive human-powered work for where it’s needed.
Intrusion detection
Detect anomalous internet traffic and respond to stop malicious activity.
Personalization
Build personalized promotions and products by analyzing customer behavior and segmentation.
Network optimization
Monitor network performance, detect and predict issues with precision. Efficiently reallocate resources in real-time.
Geospatial analysis
Tie information from documents to geospatial analysis to discover new market opportunities.
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.
- Label programmatically to solve manual labeling bottlenecks
- Continuously update and analyze models to guide development
- Adapt to real-world changes with a few clicks, not manual relabeling
Learn more
Are you ready to dive in?
Build high-quality AI 100x faster with Snorkel Flow, the AI data development platform.
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