Multimodal annotation
Use text, image, audio, video, geospatial, 3D point cloud, and 4D annotation tools to support different model-building workflows from one platform.
Appen's AI Data Platform (ADAP) for multimodal annotation, human-validated training data, fine-tuning, evaluation, automation, and expert review.
Appen's AI Data Platform (ADAP) is a flexible annotation platform for teams building AI systems with human-validated data. It combines automation and human oversight to support data production across a wide range of modalities and use cases.
The platform is designed for the full AI data lifecycle, from labelling and fine-tuning to red teaming, retrieval-augmented generation, search relevance, and other model-evaluation workflows. Appen presents ADAP as an enterprise platform for teams that need to scale data work without losing control over quality or process.
Use text, image, audio, video, geospatial, 3D point cloud, and 4D annotation tools to support different model-building workflows from one platform.
Configure task parameters, routing rules, and multi-stage reviews so the data production process matches the requirements of each project.
Combine internal experts with Appen's global crowd, supported by analytics and workforce management tools for coordinated production.
Use templates, AI-assisted annotation, and LLM integration to increase throughput while keeping human review in the loop.
Monitor contributor performance, use gold test questions, and apply smart validators to maintain quality across projects.
Connect through live API endpoints, AWS and Azure integration, webhook options, and standard APIs to fit into an existing stack.
Build labeled datasets for language, vision, audio, and multimodal models using a platform that supports multiple annotation formats and review stages.
Run model alignment and safety workflows such as SME RLHF, red teaming, and distillation with structured task routing and quality controls.
Support retrieval-augmented generation and search relevance projects that depend on human judgment, expert review, and consistent validation.
Coordinate internal specialists and external contributors in the same production process when projects need both domain expertise and scale.
Connect annotation output to downstream systems through APIs, webhooks, and cloud integrations for teams that already have an existing ML stack.
Appen positions ADAP as a flexible AI data platform that combines automation with human oversight. It is used for annotation, LLM fine-tuning, model distillation, red teaming, RAG, and search relevance work.
The source says ADAP can annotate text, images, audio, video, geospatial data, 3D point cloud, and 4D formats. It also supports specialist tooling for text annotation and extraction, audio annotation, image annotation, 3D point cloud, and 4D annotation.
Yes. Appen says ADAP includes live API endpoints, AWS and Azure integration, plus webhook and standard API options to connect to existing stacks.
Appen states that its platform supports collaboration with internal experts and Appen's global crowd, along with workforce management tools and built-in analytics.
The source does not list public pricing for ADAP, and the pricing page returned a not-found result. Based on the available pages, pricing should be treated as sales-led or not publicly stated.