Overview

The workflow uploads a sample, analyzes its distributions and correlations, then generates synthetic rows. That combination gives teams a way to create data and assess several qualities of the result, including privacy risk, rather than relying on generation alone. Synthehol says it can produce 10 million rows in about 12 seconds, a compelling throughput claim for large workloads.

The product targets healthcare, banking and finance, pharmaceuticals, insurance, retail, and load testing. Synthehol says customer data is not sold, shared, or used except to provide its services, and describes the product as built for HIPAA, GDPR, SOC 2, and ISO 27001. Enterprise adds on-premise deployment; the platform page says data never leaves the customer's environment. These claims make deployment options relevant for sensitive workloads, though teams should match the chosen plan to their own security and compliance requirements.

Key features

Generation and evaluation: Distribution and correlation analysis precede generation, and each dataset is measured for privacy, fidelity, utility, and similarity. That is useful for teams that need to judge synthetic output as well as produce it.
API and batch generation: Full REST API access and batch generation suit repeatable pipeline work better than a workflow limited to manual uploads.
Exports: CSV and JSON are included across the named plans through Starter; Parquet and Avro appear only with Professional. Teams that depend on those formats need to budget for the higher tier.
Deployment and data handling: Web, API, and self-hosted platforms give teams several integration paths. Enterprise offers on-premise deployment, while Synthehol says data never leaves the user's environment.

Pricing

The free plan costs 0.00 USD per free, billed $0/mo. It includes 1,000 credits per month, 50K rows per month, 5 projects, 5 datasets, 1 user, 1 GB storage, 30 days retention, CSV and JSON, API access, and basic support. This is a practical evaluation tier, but the 50K-row cap, single user, and short retention make it a poor fit for sustained team workloads.

Starter costs 399.00 USD per month, billed $399/mo. It raises capacity to 5,000 credits and 5M rows per month, with 25 projects, 100 datasets, 25 users, 50 GB storage, 90 days retention, CSV and JSON, API access, and email support. The extra seats and capacity suit teams moving beyond a solo trial, but this tier still lacks Parquet and Avro exports.

Professional costs 2999.00 USD per month, billed $2,999/mo. It includes 50,000 credits and 50M rows per month, 125 projects, 500 datasets, 50 users, 500 GB storage, one year of retention, all four listed export formats, API access, priority and Slack support, custom models, and advanced clustering. It is aimed at larger production workloads that can justify the substantial price increase over Starter.

Enterprise has custom pricing, with custom credits and volume pricing. It adds dedicated infrastructure, unlimited projects, datasets, users, storage, and retention, plus a dedicated account manager, phone, email, and Slack support, white label, a 99.9% uptime SLA, custom integrations, and on-premise deployment. It is the fit for organizations that need those deployment or service commitments rather than a fixed monthly tier.

Platforms

Synthehol supports API, self-hosted, and web access. The REST API and batch generation make it relevant to teams integrating synthetic data into existing pipelines; the Enterprise on-premise option serves organizations that require that deployment model. Free and paid plans include API access, while the listed export formats and support levels vary by tier.

Who it's for

Synthehol is strongest for teams that need synthetic records for ML training, QA fixture generation, or analytics and want privacy-risk, fidelity, utility, and similarity measures alongside generation. The Free plan suits initial evaluation; Starter fits modest collaborative use, while Professional is for much larger volumes and broader export needs. Organizations that require on-premise deployment, unlimited capacity, or a 99.9% uptime SLA should consider Enterprise. It is less compelling for teams whose needs fit the free cap or whose budget cannot absorb the sharp paid-plan increases.

Pros and cons

Pros: Dataset scoring covers privacy risk as well as fidelity, utility, and similarity, giving teams several dimensions for assessing output.
Pros: API access across the plans supports integration, and Professional adds Parquet and Avro for teams needing those formats.
Pros: Enterprise combines on-premise deployment with dedicated infrastructure and a 99.9% uptime SLA for organizations that need those commitments.
Cons: Free is capped at 50K rows per month, one user, and 1 GB storage, limiting its usefulness beyond evaluation.
Cons: Starter at 399.00 USD per month still restricts exports to CSV and JSON, while the next tier costs 2999.00 USD per month.
Cons: Enterprise's custom pricing makes cost less predictable than the fixed tiers.

Alternatives

Browse AI Synthetic Data Generators to compare products in the category. Choose Tabularis.AI if its free developer tier or $19.00-per-month Starter better matches your budget; its free tier includes 10,000 credits monthly, while the Starter listing gives 100,000 credits monthly. FakerForge is an option when support for Linux, macOS, or Windows matters alongside API and web access; its free tier includes 50,000 AI tokens, 100 rows per table, and 500 API requests. MOSTLY AI offers a free starting point across API, Linux, self-hosted, and web platforms. SimpleTest is a better fit for teams prioritizing test runs, with a free Starter plan that includes 50 parallel runs and 500 execution minutes monthly, but AI-generated datasets are limited to one per test. Synth Studio offers up to 1M rows per generation under its free-to-use MIT-licensed plan, making it worth considering when that cap and license suit the project. Synthetic AI Data is another free-plan option with API, self-hosted, and web platforms. Synthetic Data Vault is worth comparing for its no-cost community tier, which includes five data types, five basic constraints, nine models, and CSV and Excel support; it has no free trial. Tonic Fabricate is an alternative for teams seeking API, self-hosted, or web access with a free plan that includes $5 monthly credits and basic data exports.

Verdict

Synthehol Dataset is a strong fit for teams that need API-driven synthetic data generation with explicit measures for privacy risk and output quality. Its Free tier supports evaluation, and Professional expands volume, retention, support, and export choices. Look elsewhere if the paid tiers are beyond budget, or if the Free plan's strict row, user, and storage caps are not enough for a working team.

	Synthehol Dataset	twinify
Free plan	Yes	No
Free trial	Yes	No
Paid from	$332.50/mo	—
Open source	No	No
Platforms	api, self-hosted, Web	api, self-hosted
Free plan	Yes	—
Privacy-risk metrics	Yes	Yes
Deployment	—	self_hosted
Unstructured data	—	No

Synthehol Dataset vs twinify

Synthehol Dataset

twinify