Snorkel AI
A data development platform for frontier AI that creates specialized, high-quality training datasets and evaluation systems designed for complex, domain-specifi
- Also known as
- snorkel-ai
Available worldwide · Popular in: US
What is Snorkel AI?
Snorkel provides tools for building research-grade training data, evaluation systems, and benchmarks tailored to frontier AI models and agents. It uses programmatic data labeling with audit trails, multi-reviewer pipelines, and curriculum-structured datasets to move beyond generic coverage and address domain-specific gaps that generic models struggle with.
What Snorkel AI does
The capabilities that matter for fine tuning platforms, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Architecture model
- Managed cloud saas platform
- Peft lora and qlora parameter efficient tuning
- ✗
- Rlhf and dpo preference alignment optimization
- ✗
- Serverless hosting of fine tuned adapters lorax
- ✗
- Four bit and eight bit memory quantization
- ✗
- Flash attention and xformers compilation
- ✗
- Distributed multi GPU orchestration fsdp deepspeed
- ✗
- Synthetic data generation and evaluation pipeline
- ✓
- Native huggingface hub push pull integration
- ✗
- Weights and biases wandb experiment tracking
- ✗
- SOC2 type ii
- ✓
- Mit or apache permissive oss license
- ✗
- Pricing model
- Enterprise annual license
Platform & deployment
Independently observed- Web
- Cloud / SaaS
- Self-hosted
Integrations (10)
Independently observed- Databricks
- Snowflake
- Google BigQuery
- Amazon S3
- Google Cloud Storage
- Azure Blob Storage
- Azure Active Directory
- AWS Secrets Manager
- SAML
- OIDC
Snorkel AI alternatives
Other fine tuning platforms we track, ranked by the same independent score.
Compare Snorkel AI
Side by side against other fine tuning platforms, attribute by attribute, with a source on every value.
The Vioscale score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for Snorkel AI, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Security posture | 45 | 0.07 | 3.3 | ✓ |
| Capabilities | 46 | 0.05 | 2.2 | ✓ |
| Integrations | 30 | 0.04 | 1.2 | ✓ |
| Price level | 0 | 0.05 | 0.0 | - |
| Reliability | 0 | 0.07 | 0.0 | - |
| Pricing transparency | 0 | 0.08 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Soc2 type ii: Yes · Pricing model: enterprise_annual_license · Architecture model: managed_cloud_saas_platform · Mit or apache permissive oss license: No · Flash attention and xformers compilation: No · Four bit and eight bit memory quantization: No | mediumsource · 2026-08-21 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 10 | mediumsource · 2026-08-21 · 60% |
Market
| Attribute | Value | Evidence |
|---|---|---|
| Availability | HqCountry: US · PrimaryMarkets: … · AvailabilityScope: global · AvailableCountries: … · NotAvailableCountries: … | highsource · 2026-08-21 · 75% |
Pricing
| Attribute | Value | Evidence |
|---|---|---|
| Model | commercial | mediumsource · 2026-08-21 · 60% |