Humanloop vs Scale Rapid

Detailed side-by-side comparison to help you choose the right tool

Humanloop

🔴Developer

LLM evaluation and governance

an LLM development platform for prompt management, evaluations, logging, and trustworthy AI product iteration; the homepage announces the team joining Anthropic.

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Starting Price

Discontinued

Scale Rapid

Testing & Quality

Scale Rapid is a self-serve data annotation platform from Scale AI for getting production-quality labels quickly, with no minimums, calibration batches, production batches, and support for images, videos, text, documents, and audio.

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Starting Price

Custom

Feature Comparison

Scroll horizontally to compare details.

FeatureHumanloopScale Rapid
CategoryLLM evaluation and governanceTesting & Quality
Pricing Plans105 tiers11 tiers
Starting PriceDiscontinued
Key Features
  • Prompt management and versioning
  • Evaluation reports and CI/CD integration
  • Datasets with online and offline evaluators
  • Self-serve data annotation workflow
  • Calibration batches with feedback from Scale labelers
  • Production batches for larger-volume labeling

💡 Our Take

Choose Scale Rapid if the main problem is creating or improving labeled datasets with human annotation. Choose Humanloop if your team is primarily building LLM applications and wants a developer-focused workflow for prompt management, evaluation, and iteration.

Humanloop - Pros & Cons

Pros

  • Pricing page lists a free starting point: 2 members, 50 eval runs, and 10K logs per month.
  • Enterprise features include SSO/SAML, role-based access controls, SLA support, and VPC deployment add-on.
  • Strong fit for teams that need prompt engineering, evaluations, logs, and trustworthy LLM app iteration.

Cons

  • Homepage announces the Humanloop team is joining Anthropic and says the platform is being sunset, so new buyers must verify availability.
  • Enterprise pricing is custom and likely requires sales engagement.
  • No MCP support was visible in fetched pages.

Scale Rapid - Pros & Cons

Pros

  • Scale Rapid is documented as a distinct self-serve data annotation platform, with a product-specific documentation page at https://scale.com/docs/rapid-or-how-it-works.
  • The Rapid documentation says there are no minimums, which makes it more accessible for experimental or research labeling projects than a custom enterprise-only engagement.
  • The workflow includes calibration batches, labeler feedback, instruction improvement, quality tasks, and production batches, which gives teams a structured path from setup to larger-volume labeling.
  • Rapid supports multiple uploaded data formats, including images, videos, text, documents, and audio.
  • Scale's public pricing page lists Self-Serve Data Engine options with pay-as-you-go credit-card billing and $0 starting allocations for the first 1,000 labeling units and first 10,000 uploaded images.
  • Rapid pricing documentation explains the pricing components: fixed costs per task, variable costs per task, and project setting multipliers.

Cons

  • Scale does not publish a universal public per-task dollar rate for Rapid because task price depends on setup, labeler response, and batch configuration.
  • Use-case-specific Rapid pricing requires the Price Estimator inside the Rapid dashboard rather than a public pricing table.
  • The website is high-level and does not provide a detailed public feature matrix for Scale Rapid specifically.
  • Likely less suitable for small teams that want a simple flat monthly testing tool rather than usage-based annotation pricing.
  • The provided site content does not disclose implementation timelines, supported integrations, data residency options, or service-level agreements.

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