Cradl AI is a document AI layer for automation teams, used to turn documents into reliable structured data and drive downstream automation processes. Its core purpose is to automate document data extraction workflows, with built-in validation, review, and integration capabilities.
Main capabilities:
- Extract data from complex documents: supports handling large-volume, complex, multi-page documents, adapting to any layout and any language.
- Split and classify documents: supports line-level extraction and classification.
- Prediction safeguards: provides a confidence score for each field, supports cross-model checks to increase safety, and allows full customization of business rules through code.
- Human review: routes exceptions to business users, captures corrections, and shows the extraction source evidence for each prediction to facilitate rapid verification. Provides a dedicated interface for business users and automatically learns from each correction.
How to use: Cradl AI supports low-code automation teams while also providing developers with an API-first integration path. It can be integrated with existing automation platforms via Microsoft Power Automate, n8n, Zapier, or API. Users can get started without a credit card and can build their first agent in minutes.
Use cases: Suitable for automation teams handling critical document workflows in industries such as energy, logistics, banking, and agriculture. It can handle invoices, forms, orders, statements, reports, and other repetitive business documents. Typical use cases include: matching invoices, bills of lading, and purchase orders; managing hardware budgets; negotiating payment terms; onboarding inventory counts, etc.
Limitations and data security: User data is not used to train shared models. Through configurable settings and API, users can control data retention, access, and deletion. When prediction confidence is low, results are routed for human review, and corrections are used to improve future performance.
More details such as pricing, specific supported platform versions, and deployment methods are not yet provided.
