Mostly AI
3.83
0
MOSTLY AI generates synthetic data for privacy, AI/ML development, and fairness in analytics with its GenAI platform.
What is Mostly AI?
MOSTLY AI is a company founded in 2017 in Vienna, Austria by data scientists Michael Platzer, Klaudius Kalcher, and Roland Boubela. The company specializes in synthetic data generation using AI technology. They offer services such as creating high-quality synthetic data, prioritizing data privacy and security, providing professional training, using synthetic data for AI/ML development, and enabling cross-border data sharing. Their platform, GenAI, allows users to explore and share tabular data, contribute to fairness and bias mitigation in AI/ML, and facilitate self-service analytics. MOSTLY AI aims to revolutionize how organizations work with data by promoting the use of smart and safe synthetic data to build a smarter and fairer future for everyone.
Who created Mostly AI?
Mostly AI was founded in 2017 in Vienna, Austria by Michael Platzer, Klaudius Kalcher, and Roland Boubela, who are distinguished data scientists. They recognized the potential of AI in generating structured business data and creating synthetic data. The founders were inspired by the challenges companies faced with data anonymization, especially with the introduction of GDPR in 2018. Mostly AI's mission is to enable organizations to thrive ethically with safe synthetic data, aiming to build a smarter and fairer future with data empowerment for all.
What is Mostly AI used for?
- Data sharing
- AI/ML development
- Self service analytics
- Testing & QA
- Self-service analytics
Who is Mostly AI for?
- AI/ML developers
- Data scientists
- Software developers
- QA testers
- Data Analysts
- Testing & QA professionals
- Anyone working with synthetic data generation
- Data engineers
- Software testers
- QA professionals
- Product developers
How to use Mostly AI?
To use Mostly AI, follow these steps:
- Sign up for free on the Mostly AI platform or contact the sales team for a demo.
- Generate up to 100K rows of synthetic data daily for free.
- Access professional services and training for your synthetic data journey.
- Create synthetic data for AI/ML development to enhance fairness and explainability.
- Benefit from a platform that prioritizes data privacy and security.
- Start by using the provided sample datasets or upload your datasets to create synthetic data.
- Utilize the platform's AI-powered technology to generate high-quality, privacy-safe synthetic datasets for various use cases.
- Share synthetic data across borders without compromising privacy.
- Address biases in training datasets using algorithms to enhance fairness in AI/ML models.
- Use features like natural language interfaces for data exploration, Python client for data workflows, and creating tabular data from scratch or enriching existing datasets.
These steps ensure a smooth entry into the realm of synthetic data for various purposes like analytics, AI/ML development, product development, and software testing, all while maintaining data privacy and security.
Pros
- Easy Deployment Options
- Cross-Border Sharing
- Natural language interface
- Comes with tools like Python Client for data workflows
- Highest accuracy synthetic data
- Built for the Enterprise
- Fully anonymous synthetic data creation
- Easy integration into existing data workflows
- World's most accurate synthetic data
- Easy sharing internally and externally
Cons
- No specific cons or missing features mentioned in the document.
- No specific cons found in the provided documents.
- No specific cons were found in the document
- No specific cons mentioned in the provided information.
- No specific cons or missing features were identified for Mostly AI within the provided documents.
- No information available on cons
Mostly AI FAQs
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What is synthetic data?
- Synthetic data is artificially generated data that mimics the structure and statistical properties of real-world data without containing any actual sensitive information, ensuring privacy and security.
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How much synthetic data can you generate with MOSTLY AI for free?
- MOSTLY AI offers up to 100K rows of synthetic data generation for free every day, catering to AI/ML development, analytics, product development, and software testing needs.
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How can synthetic data contribute to fairness and bias mitigation in AI/ML?
- Synthetic data mitigates bias and enhances fairness through the use of algorithms that identify and correct embedded biases in training datasets, thereby promoting more equitable AI/ML models.
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How do you get started with creating synthetic data using MOSTLY AI's platform?
- You can get started with MOSTLY AI's platform by either using sample datasets provided or by uploading your own datasets to create your first synthetic dataset.
Get started with Mostly AI
Mostly AI reviews
Juma Abdi
December 24, 2024
What do you like most about using Mostly AI?
I appreciate the concept of synthetic data and how it helps to maintain privacy while still allowing for effective data analysis.
What do you dislike most about using Mostly AI?
The interface can be a bit complex for new users, and I found the documentation lacking in certain areas.
What problems does Mostly AI help you solve, and how does this benefit you?
It allows me to create datasets that mimic real-world scenarios without compromising sensitive information, which is beneficial for testing my ML models.
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Aisha Ngoya
December 27, 2024
What do you like most about using Mostly AI?
The ability to generate high-quality synthetic data is impressive and has been a game changer for my analytics projects.
What do you dislike most about using Mostly AI?
Sometimes, the generation process can take longer than expected, especially with larger datasets.
What problems does Mostly AI help you solve, and how does this benefit you?
It helps me overcome data privacy challenges while still being able to perform meaningful analytics, ensuring compliance with data protection regulations.
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Elijah Ochieng
November 25, 2024
What do you like most about using Mostly AI?
The concept of generating synthetic data is innovative and necessary in today's data-sensitive environment.
What do you dislike most about using Mostly AI?
I found it difficult to integrate Mostly AI with my existing data pipelines, which caused significant delays in my projects.
What problems does Mostly AI help you solve, and how does this benefit you?
It provides a way to create datasets that I can use for modeling without risking sensitive data exposure, but the integration issues are a major setback.
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