Sold by: Snorkel AI
Deployed on AWS
Snorkel's AI Data Development platform enables enterprises to develop and operationalize AI systems by transforming their own proprietary data and domain knowledge into expert evaluation and training data, and can choose between in-house data development or white-glove dataset delivery.
3
Overview
Snorkel AI empowers AWS customers to scale automation to the iceberg under the surface of valuable but unstructured enterprise data. Our unique approach equips data science and machine learning teams to adapt ML models of all sizes - including multi-billion parameter large language models (LLMs) - with their own data and expertise, accelerating AI application development up to 100x.
Deployed on AWS and leveraging AWS generative AI services, Snorkel Flow enables teams to quickly generate high-quality training sets and models over complex, highly variable, often proprietary and confidential data.
Snorkel Flow integrations with AWS include...
Seamless access to data on AWS using Snorkel Flow's native S3 connector. Prompt and fine-tune LLMs with Bedrock and JumpStart integrations. Accelerated model training, serving, and adaptability with SageMaker. Easy deployment and scalability on EKS. ... and more!
This listing enables organizations with an existing Snorkel Flow platform subscription deployed on AWS to purchase Application Units.
Planning a new AI development project? For a custom proposal reflecting your use cases and internal requirements please contact us directly at info@snorkel.ai .
Highlights
- Develop AI data programmatically - Wrangling your data is crucial and challenging, even with the latest LLMs. Snorkel Flow captures and encodes your domain expertise and automates manual tasks like filtering, curating, labeling, and slicing.
- Increase accuracy with guided error analysis - LLMs often face issues such as producing hallucinations, preventing them from being deployed in enterprise settings. Snorkel Flow gives you the tools to systematically identify errors and accurately develop data slices to improve quality and fosters innovation through multi-persona collaboration. Efficiently harness SME collective expertise by seamlessly collaborating directly with business and data science teams.
- Unify prompting, RAG, and fine-tuning - Snorkel Flow offers access to the latest open-source and closed-source models and state-of-the-art techniques like prompting, retrieval-augmented generation, fine-tuning, instruction-tuning, and pre-training within a robust, enterprise-grade platform. Streamline programmatic data curation and model customization on a single platform and make swift adjustments to fine-tune AI performance to your unique business demands.
Details
Sold by
Delivery method
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Hosted Snorkel Flow | Application Units for Snorkel Flow on AWS | $60,000.00 |
Vendor refund policy
Payment obligations are non-cancelable and non-pro-ratable for partial months and fees paid are non-refundable.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Support
Vendor support
Snorkel AI Support provides timely resolutions during business hours, 6AM PT through 6PM PT Monday through Friday, excluding U.S. public holidays.
Self-service is available via our Support Portal 24x7 where you can find documentation, how-to guides, best practices and other useful material to solve your machine learning challenges.
For more information please reference Snorkel AI Support and Maintenance Terms. Learn More:
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By Snorkel AI
By Dataloop AI/GenAI development platform
By Datasaur
Top
100
In Natural Language Processing
Top
50
In Data Preparation
Top
25
In Data Labeling Services, Software Development
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Programmatic Data Development
Automates manual tasks including filtering, curating, labeling, and slicing of unstructured enterprise data through domain expertise encoding.
Error Analysis and Data Quality
Provides systematic error identification and guided analysis tools to detect issues such as hallucinations and develop targeted data slices for quality improvement.
Multi-Model Support and Techniques
Supports access to open-source and closed-source models with state-of-the-art techniques including prompting, retrieval-augmented generation, fine-tuning, instruction-tuning, and pre-training.
AWS Native Integration
Includes native S3 connector for seamless data access, Bedrock and JumpStart integrations for LLM prompting and fine-tuning, and SageMaker integration for model training and serving.
Collaborative Multi-Persona Platform
Enables seamless collaboration between business teams, data science teams, and subject matter experts for collective expertise utilization and model customization.
Generative AI and RAG Pipeline Deployment
Deploy RAG pipelines for GenAI solutions including summarization, chatbots, and data preparation with support for RLHF and RLAIF incorporation.
Unstructured Data Management and Analysis
Explore and analyze unstructured data from diverse sources with automated preprocessing, embeddings generation, and similarity identification capabilities.
Model Versioning and Experimentation
Version, experiment, compare, and fine-tune AI models with production deployment capabilities without requiring external tool integration.
Workflow Orchestration with Drag-and-Drop Interface
Orchestrate data, models, applications, and human feedback using a drag-and-drop interface or Python SDK with pre-created pipeline templates.
Enterprise Security and Compliance
Implement GDPR, ISO 27001, ISO 27701, and SOC 2 Type II compliance with RBAC, SSO, 2FA, AES-256 encryption, and granular audit trail capabilities.
Automated Data Annotation
Support for over 250 language models for robo-labeling and automated data annotation based on custom ontologies and datasets.
Multi-Model Comparison and Evaluation
Capability to leverage multiple language models simultaneously for comparison, evaluation, and benchmarking of inference quality, speed, and cost with model recommendations.
Custom Model Development
Deployment of language models in Data Studio environment for custom model development and automation of AI solutions.
Compliance and Data Security
SOC 2 Type 2, HIPAA, and GDPR compliance certifications with data residency assurance.
Workforce Management and Monitoring
Full service workforce management and review tooling for tracking and monitoring team progress on annotation and labeling tasks.
Standard contract
No
Customer reviews
Tanbir G.
Data handler
Reviewed on Nov 09, 2023
Review provided by G2
What do you like best about the product?
It seamlessly integrates with popular machine learning libraries such as PyTorch and Tensor flow. It is a powerhouse when it comes to handle large databases. It's real strength is to handle data that is tricky and not flawless. Additionally, it's flexibility is a huge advantage.
What do you dislike about the product?
Snorkel is challenging to use as it requires understanding the concept of data labeling and weak supervision. It is not the go-to option for tasks that requires data of the highest quality. Setting up Snorkel requires effort.
What problems is the product solving and how is that benefiting you?
It enables you to handle data that is not perfect that allow to make best use of the resources in tasks where obtaining flawless data is a challenge. It helped me a lot to develop accurate machine learning model.