About
The vendor describes Snorkel as building human expert-authored datasets, evaluation environments, and benchmarks for frontier model development. The service addresses data problems including distributional gaps in specialized domains, benchmark blind spots, and failure modes that surface at scale. Snorkel delivers data two ways: off-the-shelf through "Snorkel Data Series" (curriculum-structured datasets for specific task areas with rubrics, reviewer guidance, difficulty tiers, and evaluation slices) or custom-built datasets, evaluation environments, and benchmark expansions. The page lists available datasets across terminal coding, software engineering, enterprise and workplace environments, computer use, scientific and research workflows, and STEM knowledge and reasoning. Specific offerings mentioned include Terminal-Bench 2.0 & 3.0, SWE-Bench Pro, Senior SWE-bench, τ²-bench, τ³-bench, GDPval, OSWorld 2.0, Agent's Last Exam, Terminal-Bench-Science, PaperBench, Humanity's Last Exam, and FrontierMath. Custom engagements start with analyzing what the model cannot do and where it is brittle, then include task specification, rubric design, dataset construction, RL environment development, benchmark and eval expansion, and provenance and adjudication. The vendor states datasets are built using research-backed methods.
Read from snorkel.ai on 2026-08-26. We describe what the vendor states; we do not audit it.
Enterprise Readiness
from cataloged dataNo compliance certifications listed
Flexible deployment: Cloud, On-Premise, Hybrid
8 documented integrations
5 documented use cases
Founded 2019 · Series C
Composite of public compliance, deployment, integration, adoption, and company signals. “Not disclosed” reflects gaps in available data, not a vendor deficiency.
Independently sourced
Pulled directly from regulator filings and platform APIs. No vendor or editorial input.
Enterprise Use Cases
Integrations
How Snorkel Flow compares
| Tool | Readiness | Pricing | Deployment | Compliance | Integrations |
|---|---|---|---|---|---|
| Snorkel Flow | 68 · Strong | Enterprise | Cloud, On-Premise, Hybrid | — | 8 |
| Airbyte | Not scored | Freemium | Cloud, On-Premise, Hybrid, Self-Hosted | — | 8 |
| Astronomer Astro | 70 · Strong | Enterprise | Cloud, On-Premise, Hybrid, Self-Hosted | — | 8 |
| Elastic AI | 70 · Strong | Enterprise | Cloud, On-Premise, Hybrid, Self-Hosted | — | 8 |
Peers from the same category, ranked by Enterprise Readiness. Readiness is a composite of cataloged compliance, deployment, integration, adoption, and company signals.
Frequently Asked Questions
What is Snorkel Flow used for?
Snorkel Flow is a data development service providing datasets, evaluation environments, and benchmarks for frontier AI models. It is commonly used for automated training data labeling, end-to-end ml data pipeline orchestration, compliance-driven data governance, and scaling ai model development.
Is Snorkel Flow free, and how is it priced?
Snorkel Flow uses enterprise pricing, typically a custom quote based on seats, usage, and requirements. Contact the vendor for a quote.
How can Snorkel Flow be deployed?
Snorkel Flow supports Cloud, On-Premise, and Hybrid deployment. On-premise and self-hosted options support data-residency and air-gapped requirements.
What does Snorkel Flow integrate with?
Snorkel Flow documents 8 integrations, including AWS, Azure, GCP, Snowflake, Databricks, and Kubernetes.
When was Snorkel Flow founded?
Snorkel Flow was founded in 2019 and has raised $93M in funding.
Is Snorkel Flow enterprise-ready?
Based on cataloged data, Snorkel Flow has an Enterprise Readiness score of 68/100 (Strong tier), derived from its compliance, deployment, integration, adoption, and company-maturity signals.
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