About the MOSTLY AI Tool
MOSTLY AI, an AI-powered data generator tool, has introduced a generative AI solution that is reshaping the landscape of data generation.
With its expertise in machine learning and synthetic data generation, MOSTLY AI offers organizations the power to rebalance and augment datasets.
Unlike typical mock data, synthetic datasets created by MOSTLY AI maintain the primary keys, structure, and statistical properties of the original data, making it a robust and reliable AI solution.
This ensures data privacy as these synthetic data points are not directly linked to the real data. In settings where data privacy is crucial, synthetic data stands out as a more effective approach compared to traditional anonymization techniques, upholding data utility without compromising confidentiality.
MOSTLY AI Features
MOSTLY AI is a synthetic data generation tool that offers a plethora of intriguing features tailored to meet the needs of data-driven organizations. Some of the standout features include:
- High Accuracy: Produces the most accurate synthetic data in the market.
- No Code Experience Needed: User-friendly interface that doesn’t require coding knowledge.
- Privacy-centric: Generates data that is private by design.
- Flexibility: Ability to manipulate data size, balance, and augmentations.
- Integration: Seamless integration with popular tools and platforms.
- Data Democratization: Enables widespread access to data within an organization.
- Cross-border Data Sharing: Facilitates sharing of synthetic data versions across borders and businesses.
- Data Anonymization: Provides maximum privacy and data utility.
- AI/ML Development: Synthetic training data that outperforms real data.
- Fairness and Explainability: Addresses biases and offers explainability through synthetic data.
MOSTLY AI Use Case – Real-World Applications
MOSTLY AI is the go-to tool for organizations aiming to harness the power of synthetic data. Its applications are vast and varied:
- Data Democratization: Empowers everyone in an organization to access data without privacy concerns.
- Cross-border Data Sharing: Allows sharing of synthetic data versions internationally.
- Data Anonymization: Ensures maximum privacy while retaining data utility.
- Product Development: Uses synthetic production data for improved software development.
- AI/ML Development: Provides synthetic training data for more accurate machine learning models.
- Bias Elimination: Helps in identifying and rectifying embedded biases in AI/ML models.
- Data Simulation: Enables organizations to simulate various data scenarios for testing and analysis.
MOSTLY AI Pricing
MOSTLY AI offers a diverse range of pricing plans to cater to different needs:
- Complimentary Plan: Create top-tier synthetic data at no cost, accommodating up to 100K rows daily.
- Collaborative Plan ($3.00/credit): Perfect for collaborative teams, this plan grants 1 credit for every 1 million data points, with a capacity to handle more than 1 billion data points monthly.
- Corporate Plan ($5.00/credit): Designed for extensive enterprises, it provides 1 credit for every 1 million data points and can manage over 1 billion data points monthly, complemented by specialized customer assistance.
What sets MOSTLY AI apart from other synthetic data tools?
MOSTLY AI stands at the forefront of synthetic data creation, renowned for its precise outcomes and an intuitive interface that doesn’t necessitate any coding skills.
Is synthetic data generated by MOSTLY AI privacy-compliant?
Yes, synthetic data from MOSTLY AI is private by design, ensuring GDPR compliance and maximum privacy.
How does MOSTLY AI ensure the accuracy of synthetic data?
MOSTLY AI employs sophisticated algorithms to guarantee that the synthetic data accurately reflects the statistical characteristics of genuine data.
Can I try MOSTLY AI for free?
Yes Absolutely. MOSTLY AI offers a free plan that allows users to generate up to 100K rows of synthetic data daily.
How does synthetic data benefit AI and ML development?
Synthetic data can be employed to educate machine learning models, assess biases, and supply richer and more varied datasets for AI progression.