Ascend

An Innovative Data DNA Approach

Ascend introduces an inovative data DNA technique, enabling the extraction of data insights without storing the actual data. This approach can replicate high-quality, hallucination-free synthetic data at scale, accurately reflecting the properties of original production data while ensuring compliance with legal, privacy, security, governance and data quality standards.

DNA

Use Cases

Sharing Production Data

Remote Work w/o Sharing Production Data

Cost cutting by enabling secure remote work through unique Data DNA and generating data at scale.

Curation

Data Profiling / Curation

Analyze data quality and patterns while optimizing and standardizing data for AI/ML model reliability.

tuning

Model Training / Tuning

Optimize and train ML models using privacy-compliant synthetic data that preserves statistical properties.

application testing

Product Development

Use synthetic data for application testing and development in non-production environments.

stress testing

Stress Testing

Generate synthetic data at scale for thorough product stress testing and validation.

big-data

Low Environment R&D

Enable rapid R&D using high-quality synthetic data for new innovations without regulations risk.

Deploy on Cloud or On-Prem

Easy-Integration

Easy Integration

Empower seamless automation via REST APIs, fostering effortless integration with third-party tools within our ecosystem.

deployment

Flexible Deployment

This solution seamlessly adapts to various environments, from public and private clouds to hybrid setups, and it is even deployable on-premise for maximum flexibility.

Highly-Performant

Highly Performant

 Enhanced efficiency through multi-threaded processing, parallel dataset handling, and expedited export/download options for multiple files.

Targeted Verticals

Healthcare

Clinical trial data, PHI data, patient demographics data, etc.

Finance

Credit card data, transaction records, etc.

Insurance

Claims data, policyholder data, etc.

Tech Companies

Customer PII data for app development and lower environment R&D.

Retail/E-Commerce

User behavior data, customer purchase histories, etc.

Environmental Science

Climate data, pollution data, etc.

Pharmaceuticals

Drug trial data, patient data, etc.

Telecom

Network traffic data, call record data, location data, etc.