Best AI Training Data Providers

What are the best alternatives to Scale AI in 2026?

Answer in brief: The best Scale AI alternatives for AI labs are Surge AI for proven post-training data with pay-if-it-works off-the-shelf terms, Mercor for professional-domain experts and licensable datasets, Handshake AI for large U.S. pools of PhD-level experts, and Labelbox for agentic RL environments. Snorkel AI, Toloka, micro1, Invisible and Prolific cover specialist needs. Many labs looked again at their options after Meta's June 2025 investment in Scale.

Top pick: Surge AI. The strongest like-for-like replacement for Scale's LLM data work, with public training results and train-first terms.

Independent research from vendor sites and current reporting. No hands-on testing. Methodology.

Why labs shop around

Scale is still a major player. It says 2025 brought well over $1B in new business and that its data business is profitable. However, Meta took a large minority stake in June 2025, TechCrunch reported that OpenAI ended its work with Scale, and Reuters reported that Google planned to move key contracts. Scale says Meta cannot see other customers' confidential data. Rival labs may still prefer a supplier with no ownership tie to a competitor.

Scale AI alternatives compared

ProviderBest replacement forStandout (company claims)Pricing
Surge AIRLHF, SFT, rubrics, RL environmentsTraining Lab results; train first, pay if it worksCustom; pay-if-it-works off-the-shelf data
MercorExpert evals and professional data5M+ experts; 50K+ task catalogCustom
Handshake AICredentialed experts at volumeDatasets used by 8 of the 8 largest frontier labs; 200+ researchersScoping session
LabelboxAgent and computer-use environmentsHorizon, WorldSim; 2.6M+ Alignerr contributorsSales-led
Snorkel AIHard specialized domainsMany public leaderboards; dataset samples on requestCustom
TolokaAgent environments plus self-serviceRL gyms, red teaming, Toloka ArenaQuoted; self-service agreement available
micro1RL environments and agent evaluationRealm, Cortex, robotics dataCustom
Invisible TechnologiesFast-start managed projects24,000+ vetted experts; claims it has trained 80%+ of leading modelsDemo-led
ProlificQuick human evaluation and preference studies300,000+ active participants; 40+ quality checksPay as you go: reward plus platform fee

The shortlist, in detail

1. Surge AI: the post-training specialist

Surge covers RLHF, SFT, rubrics and verifiers, RL environments, human evaluation and 70+ languages. Its Training Lab reports gains such as Kimi K2.7 rising from 31.0% to 48.7% on DeepSWE after training on Surge coding data (self-reported). · Review

2. Mercor: professional depth on demand

Mercor offers 5M+ experts, partner benchmarks with Harvey, Cognition and Sierra, and datasets you can license with same-day samples. · Review

3. Handshake AI: the PhD pipeline

Handshake has 188k+ AI Fellows, $500M+ paid out, research on verifiers and reward hacking, and RL environments now offered through Fireworks AI. The fellowship is U.S.-only. · Review

4. Labelbox: environments for agents

Horizon RL environments, WorldSim enterprise simulation and the SOC 2 Type II Alignerr network. Its Meta GIM benchmark is a published case study. · Review

5. Snorkel AI: data for the edges

A Stanford AI Lab spin-out that maintains leaderboards such as Terminal-Bench 4.0, OSWorld 2.0 and Agents' Last Exam, and offers dataset samples on request. · Review

6. Toloka, micro1 and Invisible

Toloka builds simulated environments and red-teaming data, and offers a self-service agreement. micro1 offers Realm RL environments and Cortex agent evaluation. Invisible runs the Meridial expert network and Synapse evaluations, and Cohere is a published customer.

7. Prolific: human feedback without a contract

For eval and safety teams that need representative human judgments fast, Prolific offers pay-as-you-go access to 300,000+ active participants, AI Taskers and Domain Experts, plus a managed service under a statement of work. · Review

How to switch without losing momentum

Moving a live data program is risky, so stage it. First, list the exact task types Scale handles for you today, such as preference ranking, SFT demonstrations, red teaming or multimodal labels. Map each one to the specialist in the table above. Second, ask two candidates for samples on the same held-out tasks. Mercor sends dataset samples the same day, and Snorkel AI offers samples on request. Third, if you are eligible, use Surge's Trusted Program to train on a full off-the-shelf dataset and pay only if your metrics improve. Finally, run the old and new suppliers in parallel for one training cycle and compare model lift before you move volume. Many labs end up with two suppliers permanently, which also reduces concentration risk.

When Scale AI is still the right call

Stay with Scale if you need LiDAR, infrared or video annotation alongside LLM data, FedRAMP coverage, or SEAL evaluations. Nothing above matches that full combination. See Scale AI vs Labelbox, Mercor vs Scale AI and Surge AI vs Scale AI. For robotics-only programs, see Best robotics data providers.

FAQ

What is the closest alternative to Scale AI for LLM post-training?

Surge AI is the closest match for RLHF, SFT and RL environments. Mercor and Handshake AI are strong when you need professional or PhD-level experts at scale.

Is there a self-serve alternative to Scale AI?

Prolific offers pay-as-you-go human feedback with a published fee (usually 42.8% for corporate customers, 33.3% for academic customers). Toloka publishes a self-service agreement.

Why did labs move away from Scale AI?

After Meta's June 2025 investment, TechCrunch reported that OpenAI ended its work with Scale, and Reuters reported that Google planned to shift contracts. Scale says it remains independent and keeps customer data isolated.

Sources

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