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Source profile checked Oct 8, 2026 · snapshot exported Nov 4, 2026. Importing has not reverified these facts. Original sourced profile ↗
What they do
Description
Checked Sep 29, 2026Appen supplies AI labs and product teams with human-produced training data, annotation, expert feedback, RL environments, and model evaluations for machine-learning and agentic AI systems.
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What they offer
Checked Sep 29, 2026RL environments, Human data, Evals and benchmarks, Training data, Data annotation
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Type of work
Checked Sep 29, 2026Multi-domain, Medical, Legal, Science, Finance, Coding, Browser, Security, Enterprise workflows
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Delivery formats
Checked Sep 29, 2026Datasets, API, Managed service
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Public samples and benchmarks
Checked Sep 29, 2026See sources (4)
Named customers
Checked Sep 29, 2026Amazon, Microsoft, NVIDIA, Salesforce, Adobe, Google, Meta, Apple, Pinterest
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Data handling and security
SOC 2 statement
Checked Sep 29, 2026Vendor-stated Type II
Company statement; this does not establish an independently audited report.
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Trust center
Checked Sep 29, 2026See sources (1)
Other certifications
Checked Sep 29, 2026ISO 27001:2022, GDPR, HIPAA, ISO 9001 (UK facilities), Philippines Data Privacy Act compliance
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Where it runs
Checked Sep 29, 2026Not found publicly
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Data sources
Checked Sep 29, 2026Expert or contractor-created, Licensed real-world data
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www.appen.com ↗
www.appen.com ↗
Expert or contractor-createdAppen’s global crowd of over 1 million contributors generates richly annotated data across text, audio, image, and video modalities that capture real-world nuances.
Evidence source ↗ Licensed real-world dataLicense the workflows and operational know-how your company already runs on to the AI labs building the next generation of models.
Evidence source ↗ Original fact status: listed. Check date is separate from import time.
Exclusivity
Checked Sep 29, 2026Not found publicly
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Confidentiality practices
Checked Sep 29, 2026Uses access-controlled premises and databases with logins; staff, contractors, and third parties with access to confidential information have access controls and confidentiality obligations. Enterprise-data engagements can use scoped, anonymized pipelines with named, time-limited access and audit trails.
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Company information
Headquarters
Checked Sep 29, 2026Kirkland, United States | Sydney, Australia
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Founded
Checked Sep 29, 20261996
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Company size
Checked Sep 29, 20261000+
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Latest funding
Checked Oct 8, 2026Post-IPO equity, A$50M placement plus ~A$15M share purchase plan, October–November 2024
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Total funding
Checked Sep 29, 2026Not found publicly
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