Scale AI

United States · scale.com · 15 vendors

Resilience scores

Technology vendors

Insights

Last updated 2026-07-14 · revision 2

15 direct vendors, 193 subvendors

Direct vendors by controlling owner country (sample)

Subvendors by controlling owner country (sample)

Migration Readiness: 8/10

Assessed by AI based on technology stack characteristics (cloud-native vs legacy, containerization, microservices), regulatory environment, data residency requirements, financial stability, and vendor lock-in risks. The score ranges from 0-10, where higher scores indicate better readiness for technology migration.

Scale AI exhibits high migration readiness, primarily driven by its cloud-native and containerized architecture. The company's internal tech stack is built on leading cloud platforms (AWS, Azure, GCP) and utilizes modern technologies like Kubernetes and Docker, which are foundational for portable and flexible deployments. Their products, such as the Scale GenAI Platform (SGP), are designed to be deployed on AWS, Azure, and GCP within customer VPCs, demonstrating inherent portability across major cloud environments. The development of Agentex, an open-source infrastructure framework, further underscores their commitment to flexible and less proprietary solutions, reducing potential lock-in. Scale AI's strong regulatory compliance (FedRAMP, SOC 2 Type II, ISO 27001, DoD IL4) indicates that their systems and processes are likely well-documented and adaptable to various compliance requirements during a migration. The model-agnostic nature of SGP, supporting various LLMs (OpenAI, Google, Meta, Mistral), also reduces lock-in to specific AI models, enhancing migration flexibility. Key challenges and missing information include the absence of data on financial stability, which is crucial for funding potentially large-scale migrations, and explicit data residency requirements. Similar to resilience, the 'Vendor Relationships' data is ambiguous, stating 'Total Vendors: 0' while also providing other vendor details. However, the clear adoption of a multi-cloud strategy (AWS, Azure, GCP) significantly mitigates vendor lock-in risks associated with core infrastructure, positioning Scale AI for efficient and adaptable migrations.

Compliance

12 in-scope frameworks identified; showing 3.

ITAR — Assessment Required

Scale AI has significant US defense and intelligence community contracts (CDAO, DoD IL4, BAE Systems partnership, defense AI programs). Scale AI's AI data labeling and model training services for defense applications likely involve defense articles, technical data, and defense services subject to International Traffic in Arms Regulations (ITAR) and Export Administration Regulations (EAR). Scale AI employs a global workforce of data annotators/contributors (referenced as 25% with advanced degrees from global contributor networks), which creates significant ITAR/EAR risk if defense-related technical data is accessible to non-US persons. The risk is High because: (1) ITAR violations carry criminal penalties up to $1M per violation and 20 years imprisonment; (2) EAR violations carry civil penalties up to $1.3M per violation; (3) Scale AI's global contributor model creates inherent export control risk for defense data; (4) Scale AI's partnership with BAE Systems and CDAO programs strongly implies ITAR-controlled data handling.

Evidence: https://scale.com/security, https://scale.com/public-sector, https://scale.com/blog/scale-bae-modernize-tactical-edge

EU AI Act (source) — Assessment Required

The EU AI Act (Regulation 2024/1689) entered into force on August 1, 2024, with phased implementation through 2027. Scale AI is a major AI data platform provider and AI system deployer serving EU enterprise and government customers. The EU AI Act introduces obligations for providers and deployers of AI systems based on risk classification (unacceptable, high, limited, minimal risk). Scale AI's services span multiple potentially high-risk AI application areas including: healthcare AI (Mayo Clinic patient records), defense/national security AI (CDAO, BAE Systems), employment/HR AI, and critical infrastructure AI. High-risk AI systems require conformity assessments, technical documentation, human oversight mechanisms, and registration in the EU AI database. The risk is High because: (1) Scale AI's AI systems may qualify as high-risk under multiple Annex III categories; (2) penalties for non-compliance reach €30M or 6% of global annual turnover; (3) the Act applies to providers placing AI systems on the EU market regardless of where they are established; (4) Scale AI's global public sector and enterprise EU operations are explicitly marketed.

Evidence: https://scale.com/, https://scale.com/global-public-sector, https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ:L_202401689

SOC 2 (source) — Compliant

Scale AI has publicly confirmed and actively maintains a SOC 2 Type II certification, which is the most rigorous level of SOC 2 attestation. SOC 2 Type II demonstrates that security controls were not only designed appropriately (Type I) but operated effectively over a defined audit period (typically 6-12 months). This certification is issued by an independent AICPA-accredited auditor and covers the Trust Services Criteria of Security, Availability, and Confidentiality. The risk is Low because: (1) certification is confirmed and current; (2) the report is available via Scale's Trust Center (trust.scale.com); (3) SOC 2 Type II is the gold standard for cloud service providers; (4) ongoing compliance is maintained through continuous monitoring. The primary residual risk is the gap between audit periods and any changes in the control environment.

Evidence: https://scale.com/security, https://trust.scale.com/

Financials

Three-year financials

Financial Resilience Score: 7/10

Scale AI demonstrates strong financial resilience underpinned by explosive revenue growth (from ~US$290M in 2022 to ~US$1B run-rate by end-2024) and a very well-capitalized balance sheet. The company raised roughly US$1.6B in cumulative equity funding through Series F (May 2024, ~US$13.8B valuation) and received a landmark ~US$14-15B investment from Meta in June 2025 for a 49% non-voting stake, valuing the business at ~US$29B. This provides substantial liquidity runway and strategic flexibility. Management has publicly indicated the business became cash-flow positive or near-profitable in 2024. However, resilience is tempered by significant concentration and transition risks. A majority of revenue historically came from a small number of frontier AI labs, and following the Meta transaction, competing labs including Google, OpenAI, and xAI reportedly reduced or paused work with Scale over data-confidentiality concerns—a material near-term revenue risk. The July 2025 layoffs (~14% of workforce, ~200 people) signal over-hiring correction and softening in the generative-AI data segment. Leadership transition (founder-CEO Alexandr Wang moving to Meta, replaced by Jason Droege) during hyper-growth adds execution risk. As a private company with no audited disclosures, transparency is limited. Business model exposure to contingent-workforce litigation and commoditization from competitors (Surge AI, Turing, Labelbox, Snorkel) further constrains the score. Overall, strong capital position and diversification into defense/enterprise offset near-term customer churn concerns.

Key strengths: Explosive revenue growth from ~US$290M (2022) to ~US$1B run-rate (2024), ~US$1.6B cumulative equity funding through Series F, ~US$14-15B Meta investment in June 2025 at ~US$29B valuation, Blue-chip customer roster: OpenAI, Meta, Microsoft, Cohere, U.S. DoD, Diversification into government/defense (Scale Donovan, Thunderforge $250M DoD contract), Reported cash-flow positive/near-profitable in 2024

Risk factors: High customer concentration among frontier AI labs, Post-Meta-deal customer churn: Google, OpenAI, xAI reportedly reduced/paused work, July 2025 layoffs of ~14% of workforce (~200 people), Founder-CEO leadership transition to Meta mid-2025, Contingent-workforce litigation (Remotasks/Outlier worker classification), Commoditization pressure from Surge AI, Turing, Labelbox, Snorkel competitors, No audited financial disclosures as a private company

Revenue by geography

Revenue by product/service

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