Best Sama alternatives for AI data in 2026
Sama is a managed annotation vendor known for computer vision and ethical sourcing. Here are the strongest alternatives in 2026 and where each one fits your pipeline.
The best Sama alternative in 2026 depends on what layer of your data pipeline you are filling: high-volume computer vision labeling, managed annotation with ethical sourcing, flexible crowdsourcing, or verified professional judgment. Sama is a managed annotation vendor known for computer vision and a stated commitment to responsible, impact-based sourcing of its workforce. It is a strong option for volume vision work, but it is not built for every job. If your model needs feedback from licensed professionals, the strongest alternative is a verified-expert platform like CleverX, where every contributor is a confirmed working professional. If you need flexible self-run crowdsourcing or a labeling platform you own, other vendors fit better.
A note on fairness and accuracy: This comparison uses publicly available information and secondary research as of October 2026. Vendors change their pricing, features, and positioning often, so please confirm the current details with each provider directly before you decide. We aim to be objective and fair. Every company covered here is a strong option in the space, and the best choice depends on your specific needs.
This guide covers the leading Sama alternatives, explains what each one is built for, and shows how to choose based on the task rather than the brand name. For the wider category, our overview of AI training data providers breaks down how the market is structured.
Why teams look for Sama alternatives
Sama’s core model is managed annotation: it stands up trained, dedicated teams that learn your guidelines and label data to spec, with a reputation for computer vision and for responsible employment practices. That works well for large, ongoing vision programs. Buyers move to alternatives for a few recurring reasons.
- Domain depth. Some models need feedback from practicing doctors, lawyers, or quant analysts, not a general trained workforce. When correctness depends on real professional standing, verification of that standing becomes the whole point.
- Data type. Sama’s heritage is in computer vision. Teams working on language preference data, written critiques, red-teaming, or specialist evaluation often need a different kind of contributor.
- Speed and commercial model. Managed programs take time to scope and stand up. Some buyers want on-demand, pay-as-you-go access to people who are already vetted and waiting.
- Self-serve control. Engineering teams that want to design and run their own pipelines sometimes prefer a platform plus a flexible workforce over a fully managed service.
The right alternative is the one whose core model matches the part of your pipeline you are trying to fill. The market context helps here: the data labeling and collection segment is growing quickly, with industry analysts tracking strong annual growth into the mid-2020s as labs shift budget toward higher-quality human data (see the data collection and labeling market analysis from Grand View Research).
Best Sama alternatives in 2026
CleverX (best for verified domain experts)
CleverX is an on-demand platform for verified domain professionals, built for the cases where correctness depends on real expertise. Every expert is verified through government ID, professional licence confirmation where relevant, LinkedIn experience matching, and a recorded interview, so a “senior oncologist” or “compliance officer” is actually one. The platform lists more than 10 million verified professionals and delivers the four things that modern evaluation and reinforcement learning need: evaluations, rubrics, benchmarks, and demonstrations.
CleverX is not labeling software and does not compete on commodity image tagging. It is the premium tier for expert evaluation, RLHF from professionals, red-teaming with specialists, and specialist annotation where a wrong answer is costly in regulated or technical domains. That makes it the natural alternative to Sama when your bottleneck is genuine domain judgment rather than annotation headcount. See our breakdown of domain experts for AI training by industry for how this maps to specific fields, and our guide to expert evaluations for AI training for the evaluation use case.
Scale AI (best for large managed programs)
Scale AI is one of the largest data providers, offering labeling, RLHF, model evaluation, and environments as managed programs with substantial tooling and enterprise support. In 2025, Meta took a large minority stake in the company, a deal widely reported to value Scale at roughly 29 billion dollars, which signals how much frontier labs now value human data (background on the company is on its public profile). If your priority is a single large vendor that can run an end-to-end program across many data types, Scale is a leading option. We cover it in depth in our Scale AI alternatives guide.
iMerit (best for managed specialist annotation)
iMerit provides a managed, trained workforce for annotation, with strength in domains like medical imaging, autonomous driving, and geospatial data. Its model is a dedicated team that learns your guidelines over time, which suits complex, ongoing annotation programs. Like Sama, it is a managed-services vendor rather than a self-serve marketplace, so it fits buyers who want delivery handled for them. For teams comparing Sama on its home turf of managed vision annotation, iMerit is the closest like-for-like alternative.
Appen (best for global crowd scale)
Appen is a long-established provider of crowd-sourced data at global scale, with a very large contributor network across many languages and locales. It is well suited to high-volume general labeling, localization, and broad preference data where linguistic and cultural coverage matters more than deep professional expertise. For specialist judgment tasks, most teams pair a crowd vendor like Appen with an expert platform for the parts that need it. Our Appen alternatives guide compares this category in detail.
Toloka (best for flexible crowdsourcing)
Toloka is a crowdsourcing platform with a global contributor pool and flexible task design, increasingly positioned for generative AI data and evaluation. It gives engineering teams fine-grained control over how tasks are structured and distributed, which suits teams that want to run their own pipelines rather than hand off a managed program. Its strength is scale and flexibility rather than verified professional depth. See our Toloka alternatives guide for the self-serve crowdsourcing lane.
Labelbox (best for a data platform plus network)
Labelbox is primarily a data labeling and management platform, and it also offers access to a labeling and rating network for teams that want software plus a workforce. It suits teams that want to own their annotation infrastructure and pull in human labor when needed. If your priority is tooling and workflow control rather than a managed delivery team, a platform like Labelbox is worth a look, as our data annotation platforms guide explains.
Surge AI (best for high-quality human feedback)
Surge AI has built a reputation for high-quality human feedback and RLHF, with a focus on careful task design and a more curated workforce than the largest crowd platforms. It has been cited publicly as a reference RLHF partner for leading labs. Teams that care about the reliability of preference data and written critiques often shortlist Surge. It sits toward the quality end of the crowd-to-expert spectrum, though for the hardest specialist domains a verified-professional platform still goes further.
Mercor (best for a vetted talent marketplace)
Mercor is a talent marketplace that matches vetted contractors and domain specialists to AI labs for training and evaluation work, using screening and AI interviews to filter candidates. It sits between raw crowd platforms and verified-expert platforms. If you want to place screened individual contributors on projects rather than buy managed annotation, Mercor is a strong option, and our Mercor alternatives guide puts it in context.
Comparison table
| Provider | Core model | Workforce type | Best for | Delivery |
|---|---|---|---|---|
| CleverX | On-demand verified experts | Employed professionals, verified | Expert evaluation, RLHF, specialist annotation | About 2 to 5 days |
| Sama | Managed annotation | Trained teams, responsible sourcing | Computer vision at volume | Program setup |
| Scale AI | Managed data programs | Crowd plus vetted specialists | Large end-to-end programs | Varies by program |
| iMerit | Managed annotation | Trained dedicated teams | Complex ongoing vision annotation | Program setup |
| Appen | Global crowdsourcing | Large general crowd | High-volume labeling and localization | Varies |
| Toloka | Crowdsourcing platform | Global crowd | Flexible, self-run pipelines | Varies |
| Labelbox | Platform plus network | Software plus labeling network | Owning your annotation stack | Varies |
| Surge AI | Curated human feedback | Curated crowd | High-quality RLHF and preference data | Varies |
| Mercor | Talent marketplace | Vetted contractors and specialists | Placing screened talent on projects | Varies by brief |
Workforce details and turnaround vary by project. Confirm current specifics and pricing with each vendor.
How to choose a Sama alternative
Start from the task, not the brand. Three questions narrow the field fast.
- Does the task need professional correctness or general judgment? If a wrong answer is dangerous or expensive because it takes real expertise to catch, you need verified experts. If you mainly need volume, consistency, and obvious-error checks on vision data, a managed vendor or crowd platform is more cost-effective.
- What data type are you working with? Computer vision at scale points toward Sama or iMerit. Language preference data, critiques, and specialist evaluation point toward a human-feedback vendor or a verified-expert platform.
- Do you want managed delivery or self-serve control? Managed vendors run the program for you. On-demand platforms and crowdsourcing tools give you speed and control. Match this to your team’s capacity.
Many mature AI teams use more than one vendor: a managed or crowd vendor for volume, and a verified-expert platform for the hard, high-stakes layer. The frameworks in the NIST AI Risk Management Framework and the annual Stanford HAI AI Index both underline why data quality and human oversight are now treated as core to trustworthy AI, not an afterthought.
Why ethical sourcing and quality control both matter
Sama earned part of its reputation through responsible sourcing: hiring from underserved communities and publishing standards for how its workforce is treated, an approach recognized in part through third-party certifications like the B Corp framework. That focus is genuinely valuable, and buyers who care about supply-chain ethics are right to weigh it. When you evaluate alternatives, ask each vendor how they source, pay, and support their workforce, because responsible practices and data quality tend to move together.
The second question is quality control. The metric that matters is not how many people a vendor can mobilize, but how much delivered data is usable without rework. Crowd and managed vendors typically rely on redundancy and consensus: several contributors do the same task, and agreement is treated as a proxy for correctness. That works when the right answer is obvious to a careful generalist. It breaks down when the right answer requires expertise, because a room full of non-experts can agree confidently on something wrong. In specialist domains, consensus among the unqualified is not quality control.
Verified-expert platforms invert this. Instead of averaging many uncertain opinions, they route the task to a small number of people who actually know the answer, and the verification layer, government ID, licence confirmation, LinkedIn, and a recorded interview, is what makes that routing trustworthy. For reinforcement learning from human feedback, that difference is the whole point, because the reward signal is only as good as the person producing it (the foundational work on RLHF and early systems like InstructGPT make this dependence explicit).
Where CleverX fits
CleverX is the alternative to reach for when Sama’s managed vision model is not the right shape and a crowd platform is not qualified enough. Because every expert is a verified working professional, it is built for the parts of your pipeline where domain correctness decides whether the model is trustworthy: clinical evaluation, legal and financial review, technical red-teaming, and specialist RLHF. With more than 10 million verified professionals, structured expert sessions at scale, pay-as-you-go access, and typical delivery in about 2 to 5 days, it is designed to be the premium expert layer rather than a labeling tool.
CleverX does not compete on commodity image labeling, and it does not build reinforcement learning environments itself. It supplies the experts who perform, define, and grade the work, which is the piece that is hardest to buy anywhere else. For more on that model, see our guide to sourcing experts for AI agent evaluation. If you are also weighing managed-operations vendors or AI-vetted talent platforms, our companion guides to the best Invisible Technologies alternatives and the best micro1 alternatives cover those lanes.
Train your AI with verified experts on CleverX
Frequently asked questions
What is Sama and what does it do for AI teams?
Sama is a managed data annotation company known for computer vision work and a stated commitment to responsible, ethical sourcing of its workforce. It provides trained, dedicated teams that label and curate data for AI models, often at high volume. It is a managed-service vendor rather than a self-serve marketplace or an on-demand expert platform.
Why do AI teams look for Sama alternatives?
Teams look for alternatives when their task needs something Sama is not built for, such as licensed professional judgment, fast on-demand access, self-serve tooling, or non-vision data types. Sama is strong at managed, high-volume annotation, but a model that needs clinical, legal, or financial correctness usually needs verified domain experts instead of a general trained workforce.
What is the best Sama alternative for expert evaluation and RLHF?
For high-stakes evaluation and reinforcement learning from human feedback, the best alternative is a platform where every contributor is a verified working professional. CleverX verifies experts by government ID, professional licence confirmation, LinkedIn experience, and a recorded interview, which makes it the premium tier when a wrong answer is costly because it takes real expertise to catch.
Is Sama only for computer vision data?
Sama is best known for computer vision annotation such as image and video labeling, and it has expanded into generative AI and other data types over time. If your core need is large-scale vision labeling, Sama is a strong fit. If you need preference data, written critiques, or specialist judgment, a human-feedback vendor or a verified-expert platform is usually a better match.
How do Sama alternatives differ on workforce quality?
Managed vendors like Sama and iMerit rely on trained teams and quality processes, crowd platforms like Toloka and Appen rely on scale and redundancy, and verified-expert platforms like CleverX route tasks to confirmed professionals. The right choice depends on whether your task needs volume, general judgment, or genuine domain expertise.
How should I compare pricing across Sama alternatives?
Pricing models vary from per-task and per-hour rates to managed project minimums and platform fees, and expert work costs more than generalist labeling. Rather than compare headline rates, compare cost per usable, correct data point for your domain, and always confirm current pricing directly with each vendor before you commit.