The best Scale AI alternatives in 2026

Facts checked on each company's own website, and the Meta investment in TechCrunch's report, on 24 October 2026.

Scale AI competes on several fronts at once, so the best alternative depends on what you use it for. Deepen AI Services is the alternative for teams that want a trained, in-house team on their data and a price they can see before any call: human review and data operations at a published $5 per person-hour, LLM evaluation and RLHF data from the same raters every round, and image, video and multi-sensor annotation through Deepen AI's enterprise programs. Surge AI, Mercor and Invisible Technologies compete for frontier-model data, Appen, iMerit and Sama for managed annotation, and Labelbox and SuperAnnotate for labeling software.

Why teams look for Scale AI alternatives

In June 2025, Meta invested $14.3 billion for a 49% stake in Scale AI, and Scale's CEO, Alexandr Wang, joined Meta. TechCrunch, citing Reuters, reported that Google planned to move its work to other providers and that Microsoft was reportedly pulling back. OpenAI said it would keep Scale AI as one of many vendors.

Other reasons are practical. Scale AI's site lists no prices, and you start by booking an intro call. Many teams also want the same people on their work every week, or work done inside their own tools.

The short answer: the alternative for what you use Scale for

Scale AI's competitors compared

The alternatives in detail

1. Deepen AI Services: a trained team at a published price

Where Scale AI starts with an intro call, Deepen AI Services starts with a plan by email. You describe the task, get a plan and a price within 2 working days with no sales call, then run a two-week paid pilot on your real work. The same trained, in-house people stay on your project, with a named team lead, QA sampling and a weekly report.

• Best for: Teams that want one trained team for human review, data operations, LLM evaluation and RLHF data, and automotive and robotics teams that need multi-sensor annotation and calibration.
• Who does the work: In-house teams trained and managed by Deepen AI, never crowdsourced, working inside your tools, your Ground Truth or A2I workforce, or on Deepen AI's own platform.
• Pricing: $5 per person-hour for human review and data operations, with QA and reporting included. AI evaluation, RLHF, agent and robotics data are quoted in your plan, and enterprise programs are scoped in a statement of work.
• Sensor data: Labels made once across calibrated camera, LiDAR and radar, exported to ASAM OpenLABEL, a standard Deepen AI co-authored, or your own schema. Sensor calibration as a managed service, a product or an API.
• Security: SOC 2 Type II, ISO 27001, ISO 9001 and TISAX, with work on accounts you control, under NDA.
• Track record: Running trained data teams since 2017, with more than 200 programs in production and annotation and data services delivered for Daimler Trucks, BMW, Bosch, Mercedes, Hexagon, Aptiv and Ford Otosan.

See the full Scale AI vs Deepen AI comparison.

2. Surge AI: frontier-model data

Surge AI competes with Scale AI's generative AI work. It sells frontier data off the shelf and runs post-training projects and RL environments with an expert workforce. Like Scale AI, it publishes no prices, and the first step is its contact page.

3. Mercor: expert human data and evaluations

Mercor competes for the expert work behind frontier models: physicians, lawyers and engineers who write and grade training data and evaluations. Instead of client prices, it lists the hourly rates it pays experts by role, around $100 on average.

4. Invisible Technologies: training data with vetted experts

Invisible pairs training data and RL environments with Meridial, a pool it describes as 24,000+ vetted experts, and says it has trained over 80% of the world's leading AI models. Like Scale AI, it begins with a demo.

5. Appen, iMerit and Sama: managed annotation

For Scale AI's annotation business, the managed alternatives are Appen, with coverage of more than 500 locales; iMerit, part of EXL, for image, video and LiDAR work and generative AI services; and Sama, a Certified B Corp, for vision, multimodal and sensor data. All three start with a conversation and publish no prices.

6. CloudFactory: managed teams on annual commitments

CloudFactory's managed teams compete for ongoing work. Where Scale AI opens with an intro call, CloudFactory opens with a free analysis of a sample of your data, then prices on annual spend commitments.

7. Toloka: data for AI agents and LLMs

Toloka competes with Scale AI's agent and LLM data: demonstrations, preference data, red-teaming and expert work. It also starts with a conversation and lists no prices.

8. Labelbox and SuperAnnotate: platforms

If you used Scale AI's platform to label data yourself, Labelbox and SuperAnnotate are the software alternatives. Labelbox has moved toward training environments, robotics data and its Alignerr expert network, and SuperAnnotate sells Starter, Pro and Enterprise plans through its sales team.

How to move work off Scale AI

• Export your datasets, labels and any evaluation results in a format you control
• Save your guidelines, rubrics and taxonomy, with examples of work you accepted and rejected
• Keep a gold set of items with known answers to check the new provider against
• List each workstream with its weekly volume, turnaround and data types
• Run a pilot on real items next to your current work before you move full volume
• Compare pilots on the cost of each accepted label, including your own review time

For prices across providers, see data labeling pricing in 2026.