Feed business systems and automation workflows
Structured field data exports as JSON or CSV, clean, validated, and ready for immediate use in ERPs, databases, or agentic workflows.
Data output

Extracted and validated document data has to reach the systems your processes rely on (ERP, CRM, automation platforms, agentic workflows, or AI models), ideally without manual intervention. ABBYY Document AI closes that last mile, automatically exporting data in the format each downstream system requires and delivering it via REST API or pre-built connectors from the ABBYY Marketplace.
Structured field data exports as JSON or CSV, clean, validated, and ready for immediate use in ERPs, databases, or agentic workflows.
Doclang delivers a machine-readable representation of the full document with structure, layout, and governance metadata included, so LLMs and AI agents work from verified facts, not inferred approximations.
Recognized text exports to DOCX, XLSX, HTML, and other editable formats with the original document structure preserved.
Processed images export as searchable PDFs and PDF/A for retrieval and long-term archival and deliver directly to SharePoint or shared storage. Sensitive fields can be permanently redacted before export where compliance requires it.

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Increase straight-through document processing with data-driven insights
Integrate reliable Document AI in your automation workflows with just a few lines of code
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Validated data needs to reach its destination whether that's a decades-old ERP, a homegrown platform, a specialist line-of-business application, or an agentic workflow orchestrator. Pre-built connectors cover the most common enterprise systems with minimal integration effort. For anything else, an open API gives development teams the flexibility to build what's needed. Either way, data arrives in the format the receiving system expects.
Most business processes start with a document - an invoice that needs approval, a contract that triggers an obligation, a form that opens a case. When structured data exports directly into the systems that act on it, the document becomes the event that drives the process forward. Approvals are routed, cases opened, and obligations tracked, creating an end-to-end process fueled by the data within the document.
Data is encrypted in transit and validated against your business rules before export, ensuring only clean, compliant data reaches downstream systems, with discrepancies flagged for human review. Where required, specific fields can be permanently redacted before export, with the underlying data irrecoverable from the exported file. Audit trails stay intact and regulatory obligations, such as GDPR, CCPA, and sector-specific requirements, are met without manual gatekeeping.
For product and development teams, ABBYY's output capabilities can be embedded natively into your own application—so structured data reaches end users as part of your product experience, not a connected system alongside it.
Data output is the final step in the ABBYY IDP pipeline. Once your documents have been processed, classified, and validated, structured data is ready to leave the system and go to work.
This is where extraction delivers its business value. Validated data is automatically formatted for its destination and exported to the systems, workflows, and AI pipelines that act on it — completing the journey from document to decision.
Purpose-built AI extracts data from any document type and validates it against your business rules. Discrepancies are flagged; clean data moves forward automatically.
Validated data is structured into your required output format—JSON, CSV, Doclang, or others—ready for the specific system or workflow receiving it.
Data is exported securely to your destination of choice—REST API, SFTP shared folder, ODBC database, SharePoint, or an external system via Marketplace connector or custom script—initiating the next step without human handoff.
How combining purpose-built Document AI with LLMs creates end-to-end workflows that are both accurate and contextually rich.

Why clean, structured document data is the prerequisite for reliable AI agents—and how continuous improvement keeps the system getting smarter.
What happens when IDP doesn't just extract data but equips autonomous agents to decide what to do with it—automatically, across end-to-end workflows.
Why clean, structured document data is the prerequisite for reliable AI agents—and how continuous improvement keeps the system getting smarter.
Exports fall into four categories.
ABBYY supports multiple delivery destinations: REST API, SFTP-accessible shared folders, ODBC-compatible databases, SharePoint, and external systems via pre-built Marketplace connectors or custom integration scripts. Export runs automatically as documents complete processing or can be triggered manually, with configuration handled at the project or workflow level.
Doclang is an open, AI-native document format developed by an industry working group including ABBYY, IBM, Nvidia, and Red Hat. Unlike PDFs or HTML, it explicitly defines document structure, layout, and semantic meaning in machine-readable form—making it the preferred output when document data feeds LLMs or AI pipelines. It reduces hallucinations by grounding model inputs in verified content and embeds governance metadata, such as PII flags and model usage policies, directly in the file.
Data is encrypted in transit and validated against your business rules before leaving the platform. Specific fields can be permanently redacted before export, appearing as blacked-out areas in exported images with the underlying data irrecoverable. This supports compliance with GDPR, CCPA, and sector-specific requirements without manual oversight at the point of export.
Yes. Export workflows can be configured to initiate downstream actions—approval routing, report generation, compliance flagging—based on the content and status of exported data, extending automation from document processing into the business processes that depend on it.
Data is validated against your business rules before export. If a discrepancy is detected—a missing field, an out-of-range value, or a rule violation—the document is flagged for human review rather than passed downstream, protecting data integrity across your workflows.
Schedule a demo and see how ABBYY intelligent automation can transform the way you work—forever.
How combining purpose-built Document AI with LLMs creates end-to-end workflows that are both accurate and contextually rich.

What happens when IDP doesn't just extract data but equips autonomous agents to decide what to do with it—automatically, across end-to-end workflows.