Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
Secludy PII-Free Synthetic Text Replicas Free trial
By:
Latest Version:
v.1.0.2
Protects sensitive corporate data through generating replacement with differential privacy
Product Overview
NOTE: This is the evaluation version of our Privacy-Guaranteed Synthetic Data Product. The evaluation includes a 30-day free trial. Contact us at support@secludy.com for information on our full-version pricing plans. Secludy Privacy-Guaranteed Synthetic Text Data Replicas is an enterprise-grade solution for generating privacy-safe synthetic data from sensitive business information. Unlike traditional data anonymization approaches, Secludy creates high-quality synthetic examples that preserve essential patterns while providing mathematical privacy guarantees. Ideal for organizations in healthcare, finance, and other regulated industries that need high-quality, privacy-safe data for AI development. Secludy transforms sensitive business data into valuable AI training resources while maintaining strict privacy standards.
Key Data
Version
By
Type
Algorithm
Highlights
Top use cases:
- Creating privacy-safe email datasets for spam detection
- Generating synthetic customer communications for sentiment analysis
- Developing test datasets containing realistic but safe PII/PHI
- Augmenting limited sensitive datasets with privacy-protected examples
Key benefits:
- Maintains statistical relationships in original data
- Provides provable privacy guarantees
- Generates domain-specific content at scale
- Preserves data utility for downstream AI tasks
- Ensures regulatory compliance
The solution enables organizations to:
- Scale AI development without privacy risks
- Share data safely across teams and organizations
- Test systems with realistic but safe data
- Accelerate AI projects while protecting sensitive information
Not quite sure what you’re looking for? AWS Marketplace can help you find the right solution for your use case. Contact us
Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Contact us to request contract pricing for this product.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Algorithm Training$10/hr
running on ml.g5.xlarge
Model Realtime Inference$16.00/hr
running on ml.p3.2xlarge
Model Batch Transform$16.00/hr
running on ml.p3.2xlarge
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Algorithm Training$1.408/host/hr
running on ml.g5.xlarge
SageMaker Realtime Inference$3.825/host/hr
running on ml.p3.2xlarge
SageMaker Batch Transform$3.825/host/hr
running on ml.p3.2xlarge
About Free trial
Try this product for 30 days. There will be no software charges, but AWS infrastructure charges still apply. Free Trials will automatically convert to a paid subscription upon expiration.
Algorithm Training
For algorithm training in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Algorithm/hr | |
|---|---|---|
ml.g5.xlarge Vendor Recommended | $10.00 |
Usage Information
Training
Input dataset should be formatted as JSONL (JSON Lines) with column of "content" and "category"
for example: {"content": "From: Liam O'Connor liam.oconnor@costco.com\nTo: Operations Team operations.team@costco.com\nSubject: Update on Warehouse Optimization Project\n\nThe new layout plans are finalized and ready for implementation next week. Please review and prepare your teams accordingly.", "category": "Project Updates"} To download test input data
Metrics
Name | Regex |
|---|---|
loss | 'loss': (\d+\.\d+) |
Channel specification
Fields marked with * are required
training
*Input modes: File
Content types: -
Compression types: None
Hyperparameters
Fields marked with * are required
epochs
*Number of training epochs
Type: Continuous
Tunable: Yes
batch_size
*Training batch size
Type: Integer
Tunable: No
learning_rate
*Learning rate for optimization
Type: Continuous
Tunable: Yes
grad_accum_steps
*Number of gradient accumulation steps
Type: Integer
Tunable: No
epsilon
*Epsilon parameter for training
Type: Continuous
Tunable: No
max_seq_length
*Maximum sequence length for input processing
Type: Integer
Tunable: No
instruction
*Classify the following email content into its appropriate category based on its content.
Type: FreeText
Tunable: No
Model input and output details
Input
Summary
A json file containing which category to generate, how many copies for each category, and generation output length.
Input MIME type
application/jsonSample input data
{
"categories": [
"Project Updates",
"HR Communications"
],
"num_replicas": 1,
"max_tokens": 500,
"instruction": "write me some corporate email examples in the category of"
}Output
Summary
Model will minic training data structure, tone, format, and internal statistical relationship to generate high fidelity PII free synthetic replias.
Output MIME type
application/jsonlinesSample output data
{
"category": "Project Updates",
"example": "From: John Doe <john.doe@costco.com>\nTo: Project Team <project.team@costco.com>\nSubject: Update on Q4 Sales Target Projections\nContent: I'm pleased to inform you that our revised projections for the Q4 sales targets have been completed. The team's diligent work has resulted in a 12% increase in our projections, a significant improvement that will boost our quarterly revenue. I appreciate everyone's efforts and dedication. Let's maintain this momentum as we continue to drive our sales growth.\n\n---"
},Sample notebook
End User License Agreement
By subscribing to this product you agree to terms and conditions outlined in the product End user License Agreement (EULA)
Support Information
Secludy PII-Free Synthetic Text Replicas
support@secludy.com
Personal phone numbers of founders are also available 24/7 for support : )
AWS Infrastructure
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.
Learn MoreRefund Policy
We offer a great 30-day free trial. After the free-trial, no refunds can be made
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