Scale AI vs Encord: which one should collect your robot training data?
Last updated: 2026-11-09 · Independent research based on each company's own public pages. We did not test either service.
Answer in brief: Choose Scale AI if you want the highest stated collection throughput and data from many embodiments and locations. Scale says 1,000+ hours of demonstration data reach its platform every day, from data factories, at-home collectors and in-field commercial deployments. Choose Encord if you want a collection protocol designed and piloted in a Bay Area lab, operators running tasks on your robot, and episodes that land directly in the platform your engineers already use to curate and label. Both collect teleoperation and egocentric data, both annotate, and both quote collection privately.
Top pick for volume and embodiment diversity: Scale AI. Data factories, residential collectors, in-field rigs, teleoperated bimanual manipulators, the robotless Scale Harness, and a white-glove option where Scale operates your own hardware.
The head-to-head at a glance
| What matters | Scale AI | Encord |
|---|---|---|
| Where collection happens | Data factories (centralized, high volume), residential at-home collectors, in-field commercial and industrial deployments | Bay Area lab pods (kitchen, laundry, industrial), in-field operators in kitchens, warehouses, offices, vehicles and industrial sites, plus on-site at your factory or warehouse |
| Embodiments | Teleoperated bimanual manipulators, the Scale Harness egocentric rig, or your hardware managed and operated by Scale | Your robot (embodiment-specific), stationary and mobile leader/follower teleop arms, UMI handheld grippers including multi-finger and client-provided hardware |
| Egocentric capture | Scale Harness, designed for distributed dexterous collection | Head and wrist cameras at 1080p/30FPS. Base kit: RGB-D stereo depth cameras with IMU and multi-camera sync |
| Stated scale | 1,000+ hours per day uploaded; scales to thousands of collectors; petabyte-scale ingest | Thousands of trained in-field operators; 300+ AI teams use the platform |
| Delivery | Grounding annotations; listed datasets go through Scale's internal policy fine-tuning and evaluation | Data flows straight into Encord's platform; native MCAP and ROSBAG; VLA output as structured JSON |
| Feedback loop | In-house roboticists help write data specs | Field failures captured through remote teleoperation and fed back into collection and annotation policies |
| Security | SOC 2 Type II, ISO 27001; supports GDPR and CCPA; optional onshore processing | SOC 2 Type II, HIPAA, GDPR; VPC, on-prem and air-gapped options |
| Pricing model | Custom quote (book a demo) | Platform tiers (Starter, Team, Enterprise) on a public pricing page; collection quoted per protocol |
Scale AI: built for labs that need breadth, fast
Scale's pitch is throughput plus diversity. It draws on three collection environments (data factories, homes and operating businesses), so one program can cover very different settings. On the hardware side, you can choose teleoperated bimanual robots, the robotless Scale Harness for distributed dexterous capture, or have Scale run your hardware. Collection cells are developed and validated in Scale's San Francisco R&D lab before they go out to its global partner network. Scale names Generalist and Physical Intelligence as users of its data platform. It also says datasets are run through its own policy fine-tuning and evaluation before they are listed, a strong signal for teams that want data already checked against a model.
Encord: collection wired straight into your data stack
Encord designs the collection protocol backwards from your training pipeline. Tasks, hardware and quality criteria are defined with your team and piloted in its lab before operators go into the field, so you don't pay to recollect data that misses the target. It collects four data types: embodiment-specific, teleoperation, egocentric and UMI. The embodiment-specific mode, where operators run daily tasks on your own robot, is the closest match to a single deployment configuration. Episodes land directly in Encord's curation and annotation platform with no ingestion step. After launch, remote teleoperation captures field failures and turns them into new collection jobs.
When to pick which
- Pick Scale AI if you are training a generalist or foundation policy and need many embodiments, environments and hours every day, with a dedicated engineering and operations team running at your pace.
- Pick Encord if you are fine-tuning for one robot or one deployment, want collection and labeling in a single tool, need native MCAP or ROSBAG, or require VPC or air-gapped deployment.
- Consider both if you want broad pre-training data from one vendor and embodiment-specific fine-tuning data plus deployment feedback from the other.
Pricing model
Neither company publishes a rate card for collection. Scale is demo-led. Encord's pricing page lists Starter, Team and Enterprise platform plans (VPC and on-prem are Enterprise options) but no dollar figures, and collection is scoped per protocol. See our robotics data pricing guide.
FAQ
Does Scale AI or Encord collect teleoperation data?
Both do. Scale offers teleoperated demonstrations from bimanual manipulators. Encord uses leader/follower teleoperation machines, both stationary and mobile, operated by trained humans in its lab facilities.
Which can collect on my own robot?
Both. Scale offers bespoke collection platforms where your hardware is managed and operated by Scale. Encord's embodiment-specific mode has operators run daily tasks with your robot, including on-site at your factory or warehouse.
Which has more stated scale?
Scale publishes the more specific number: 1,000+ hours of demonstration data uploaded every day. Encord says it has thousands of trained in-field operators.
Is there public pricing?
Not for collection. Encord publishes platform plan tiers without prices. Both quote collection after scoping.
Keep comparing
See the full ranked list of robotics data providers · Scale AI vs Appen · Alternatives to Scale AI · How to choose
Sources
- scale.com/physical-ai
- encord.com/physical-ai-data
- encord.com/data-collection
- encord.com/pricing
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