MOSTLY AI

MOSTLY AI is a synthetic-data platform for teams that need connected datasets, analysis tools, and control over where generation runs. It is best suited to organizations working with relational data and varied deployment environments; the main trade-offs are demanding Kubernetes resources and Linux-only GPU support in local SDK mode.

Overview

Founded in Vienna in 2017, MOSTLY AI brings synthetic and mock data generation together with access to production data and data analysis. Its Apache v2-licensed open-source Python SDK supports local generation, while the platform can run on Kubernetes or OpenShift, or be installed through Minikube on a single VM. Hybrid deployment, private cloud, and on-premises installation—including air-gapped environments—make it a strong fit for organizations that need deployment flexibility. A single-node Kubernetes installation, however, requires at least 24 CPU cores, 48 GB of RAM, and 256 GB of storage, a serious infrastructure commitment.

Key features

The platform supports numerical, categorical, and date-time data, along with text and geolocation. Its ability to synthesize multiple related tables while preserving their relationships is valuable for teams whose test datasets need to reflect connected databases, rather than stand-alone tables.

Data Insights Reports, data rebalancing, missing-value imputation, and generation temperature control provide ways to inspect and shape output. A natural-language assistant can create and run Python code for data analysis, extending the product beyond generation. For workflows that need to connect generation to existing systems, connectors cover MySQL, PostgreSQL, MariaDB, Oracle Database, Microsoft SQL Server, Snowflake, Databricks, BigQuery, Apache Hive, and Azure, GCP, and AWS cloud buckets. The API and Python client support application and workflow integration; CSV, Parquet, and XLSX are supported formats.

The SDK's local mode supports GPU acceleration only on Linux. That restriction matters to teams planning local generation on other operating systems, even though the product's platform options also include web, API, and self-hosted deployments.

Pricing

MOSTLY AI uses a freemium model. The Free plan costs nothing and is presented as a way to get started; it has no stated seat, quota, or usage limits. Teams comparing it with paid offerings should not assume that an unstated cap applies—or that the free plan covers a particular workload. Support is available by email at [email protected].

Platforms

MOSTLY AI is available through web, API, Linux, and self-hosted options. Kubernetes and OpenShift deployment, Minikube installation on a single VM, private cloud, and on-premises installations provide several ways to place the platform. Its stated security credentials include SOC 2 and ISO 27001 certification.

Who it's for

MOSTLY AI is a practical candidate for teams that need synthetic relational datasets, analysis capabilities, and deployment choices ranging from hosted access to air-gapped on-premises environments. It is less suitable for organizations seeking a low-resource Kubernetes installation or local SDK GPU support on a non-Linux system.

Pros and cons

• Pros: Multi-table synthesis preserves relationships, making output more useful for connected database workflows.
• Pros: Analysis tools, a natural-language Python assistant, API access, and broad database and cloud-bucket connectors support work beyond standalone generation.
• Pros: Hybrid, private-cloud, and air-gapped deployment options accommodate differing infrastructure needs.
• Cons: Single-node Kubernetes needs at least 24 CPU cores, 48 GB RAM, and 256 GB storage, putting it beyond modest infrastructure.
• Cons: GPU support in local SDK mode is restricted to Linux.
• Cons: The Free plan's workload capacity cannot be judged from its stated terms.

Alternatives

AI Synthetic Data Generators and Synthetic Data Generation Software are useful category lists for comparing other synthetic-data products. For a broader testing focus, see Test Data Management Software, Data Masking Software, and Test Data Generation Tools.

• FakerForge is another freemium option, with a free monthly plan that states database, token, row, table, API-request, and mock-API limits.
• REaLTabFormer is a free, MIT-licensed Python option for Linux, macOS, Windows, and self-hosted use.
• Synth Studio is free to use and sets a limit of up to 1M rows per generation.
• NVIDIA ShadowPlay is a free Windows option with stated Windows, driver, and supported-GPU requirements.
• SimpleTest is a freemium testing option whose free Starter plan includes 50 parallel test runs and 500 execution minutes per month, with AI-generated datasets limited to one per test.
• Synthehol Dataset is a free API, web, and self-hosted option with monthly credit and row caps, project and dataset limits, and 30-day retention.
• SynthEngyne offers monthly free credits, with different credit consumption for text, tabular, time-series, and image data.
• Synthetic AI Data has a free plan and supports API, self-hosted, and web platforms.

Verdict

Choose MOSTLY AI if your team needs relational synthetic data, analysis and integration tools, and the option to run in controlled or isolated environments. Its breadth is compelling, but the Kubernetes resource floor and Linux-only local GPU support make it a poor fit for teams with modest infrastructure or a need for cross-platform local GPU generation.