Document Agents

True language comprehension. No template matching.

At a Glance

99.1% Zero-Touch

Routine documents processed autonomously - no manual post-processing

20+ Document Types

Invoices, contracts, sick notes, tax assessments, receipts, and more

True Comprehension

Contextual language understanding instead of OCR template matching

Decision Layer

Every extraction with confidence score, rule version, and audit trail

Model-Agnostic

Claude, ChatGPT, Gemini, Llama - model is interchangeable

SAP, DATEV, Workday

Integration via APIs - agent logic decoupled from the target system

Definition: Document Agent

A Document Agent is a specialized AI agent for automated processing of enterprise documents. It uses Large Language Models (LLMs) for contextual language understanding - not template matching, not rigid OCR rules.

The Document Agent reads a document, understands its content, and makes a professional assessment. This assessment is verified via the Decision Layer, documented, and written to the audit trail.

What Document Agents Process

Incoming invoices and credit notes
Sick notes and medical certificates
Employment contracts and amendments
Certificates and supporting documents
Receipts and travel expense reports
Tax assessments and official correspondence

How a Decision is Made

Document    →  Agent reads     →  Decision Layer checks
(Invoice)      and understands    completeness, plausibility,
tax classification
│
┌────────────┴────────────┐
│                         │
High Confidence          Low Confidence
Clear rule              or exception case
│                         │
Posting proposal         Escalation to
+ Audit Trail           clerk

With high confidence and clear rule application: autonomous processing with complete audit trail. With low confidence, exceptions, or missing information: escalation to a clerk - with all the context the agent has already extracted. In combination with a Workflow Agent, the entire process is orchestrated end-to-end.

Decision Layer for Documents

Every document processing creates a complete decision record:

Input: Document hash, document type, extracted fields
Ruleset: Applied rule, version, timestamp
Assessment: Confidence score, risk score
Result: Posting proposal or escalation
Routing: Autonomous decision or human-in-the-loop

The Document Agent doesn't replace clerks - it handles routine cases autonomously and escalates exceptions to humans, with full documentation. Learn more about the Decision Layer architecture.

Document Agent vs. OCR vs. Manual

	Document Agent	OCR System	Manual Processing
Comprehension	Contextual - understands content and meaning	Character recognition + template matching	Full cognitive capability
Free-text / Handwriting	Yes - true language comprehension	Limited - breaks on deviations	Yes
Speed	Seconds per document	Seconds, but often requires post-processing	5-10 minutes per document
Scaling	Linear with volume	Linear, but manual on errors	Only with more staff
Audit Trail	Automatic per decision	Limited	Manual, often incomplete

In Practice: Incoming Invoices

Scenario: 500 incoming invoices per month

Before (manual)

8 minutes per invoice (review, posting, verification)
~67 hours per month
Posting error rate: 4-6%
Audit trail: Excel spreadsheet, manually maintained

After (Document Agent)

99.1% processed autonomously (495 of 500 invoices)
<1% escalated to clerks (~5 invoices/month)
98% of all follow-ups with the document sender resolved autonomously
<0.5h manual effort per month
Error rate: below 0.3% (rule-based posting)

Result: From 67 hours down to under 30 minutes per month. The agent posts, verifies, and books autonomously. When information is missing (e.g. PO number, cost center), the agent follows up with the document sender directly - 98% of these queries are resolved without human intervention. Only genuine exceptions reach a clerk.

Human-in-the-Loop

Agent decides: Posting, booking proposal, payment terms, follow-ups with document sender.
Human decides: First-time vendor approval, invoices above approval threshold, deviations from order value >5%.

Use Cases

Finance & Accounting

Invoice processing, posting, document verification. Integration with DATEV and SAP FI/CO. Pre-configured solution: Finance AI Agents.

HR & People Operations

Sick notes, contract documents, certificates. Integration with SAP SuccessFactors and Workday. Pre-configured solution: HR AI Agents.

Compliance & Audit

Automatic verification of incoming documents against internal policies and external regulations. The Decision Layer documents every verification decision.

Integration

Document Agents connect to existing systems via standardized interfaces:

SAP FI/CO, SAP S/4HANA
DATEV
SAP SuccessFactors, Workday
SharePoint, Microsoft Teams
Email inboxes (IMAP/Exchange)
Others via REST/SOAP

Agent logic is decoupled from the target system. Switching your ERP changes the export layer - not the agent. Need an agent for a process not covered by the three standard types? Co-Build delivers custom agents in 4-6 weeks.

Other Agent Types

The Coordinator

Workflow Agents

Orchestrate processes across systems - SAP, DATEV, SharePoint.

Details

The Knowledge Carrier

Knowledge Agents

Answer questions from rule sets - with source citation and rule version.

Details

Custom Agents

Co-Build

Your process, your agent. 4-6 weeks to a productive agent.

Details

Deep Dive in the Agent Briefing

Our article series for decision-makers implementing AI agents in the enterprise.

Infrastructure

RAG & Document Intelligence: How AI Understands Your Documents

Read

Governance

PII Anonymization for Enterprise AI

Read

Governance

Decision Layer - What It Is and Why Every Enterprise AI Agent Needs One

Read

Document Agent FAQ

What is a Document Agent?

A Document Agent is a specialized AI agent that reads, understands, and processes enterprise documents with true language comprehension. It doesn't replace clerks - it handles routine cases autonomously and escalates exceptions to humans, with full documentation via the Decision Layer.

What documents does a Document Agent process?

Incoming invoices, credit notes, sick notes, employment contracts, contract amendments, certificates, receipts, tax assessments, and other structured and unstructured business documents.

How does a Document Agent differ from OCR?

OCR recognizes characters on an image. A Document Agent understands content: it identifies the document type, extracts relevant data, checks factual plausibility, and makes a classification decision. Every decision is documented via the Decision Layer and is auditable.

Which documents should your first agent process?

Talk to us about your specific use case.