An AI agent is a software system that processes information and, within defined parameters, can independently carry out tasks and trigger actions. In a business context, AI agents can, for example, review documents, verify information, or initiate further steps in a process.

What is the difference between agentic AI and generative AI?

Generative AI creates new content, such as text or summaries, based on input. Agentic AI goes a step further: It uses AI models and other tools to pursue a defined goal and carry out multiple steps to achieve it.

What is the difference between IDP and Agentic AI?

Intelligent Document Processing focuses on understanding documents, classifying them, and extracting relevant information. Agentic AI can build on this information and take on additional tasks within a business process.

Can AI agents process documents automatically?

Yes. When used in conjunction with Intelligent Document Processing, AI agents can utilize information from documents, verify results, and trigger further process steps depending on the specific use case.

Which processes are suitable for Agentic AI?

Of particular interest are document- and communication-intensive processes involving many recurring decisions and manual intermediate steps—for example, in purchase-to-pay, insurance, financial services, manufacturing, or business process outsourcing.

How do you implement AI agents in a company?

It is common to start with a well-defined subprocess that handles a large volume of transactions and produces a measurable result—such as the account assignment of incoming invoices. This requires a reliable understanding of the incoming documents, as well as clearly defined boundaries within which the agent is allowed to make decisions on their own.

What distinguishes AI agents from automation based on fixed rules?

Rule-based automation requires a separate set of rules for each variant. An AI agent, on the other hand, makes decisions based on the specific process and can therefore handle cases that were not previously described. This significantly reduces the effort required for customization.

Agentic AI
- LLMs
  - The Foundation of Intelligent Speech Processing
Solutions
- Automation Platform
  - Intelligent Process Optimization
- Response Management
  - From the Inbox to Autonomous Customer Communication
- E-Invoicing
  - From Invoice Receipt to an Autonomous Financial Process
- Mobile
  - Efficient E-Health Solutions
- Cloud
  - Insiders Cloud Services – Anywhere, Anytime
Services
- GenerAItor
  - Build powerful AI solutions yourself
- Marketplace
  - Find the right automation service
Industries
- Insurance
  - From Claim Filing to Final Settlement
- Banking
  - From Sales Order to Case Closure
- E-Health
  - From Document Receipt to Streamlined Administration
- Industry
  - From Order Receipt to Automated Order Processing
- Public
  - From Application Submission to Digital Decision
References
Events

Language

Agentic AI

Lösungen

Services

Branchen

KI Agenten

LLMs

Automation Platform

Response Management

E-Invoicing

Mobile

Cloud

GenerAItor

Marketplace

Versicherungen

Banken

Gesundheitswesen

Industrie und Handel

Öffentlicher Sektor

Agentic AI: AI Agents for Document-Based Processes

Understanding documents, extracting information, automating processes—that’s the foundation. With Agentic AI, Insiders takes it a step further: AI agents independently perform tasks, verify results, and trigger further actions. This transforms Intelligent Document Processing (IDP) into an intelligent, agent-based process.

When AI Not Only Understands but Also Acts

Agentic AI refers to AI systems that work autonomously toward a goal within a defined framework. An AI agent can analyze information, incorporate various data and systems, prepare decisions, and trigger the next steps in the process based on the outcome.

This offers significant potential, particularly in document-intensive business processes: documents are no longer merely recognized, classified, and parsed. AI agents can review and verify the information obtained and derive concrete actions from it—ranging from the next process step to a targeted inquiry when information is missing.

This makes Agentic AI relevant wherever documents and the information they contain drive business processes—for example, in insurance and banking, industry and retail, healthcare, or the public sector. AI agents can be deployed across industries and tailored to the respective documents, processes, and business requirements.

Agentic AI for Your Industry

Verification

Agentic Verification – More Touchless Processing

What happens when an extraction result isn’t clear enough for fully automated further processing? Today, that means manual review. Agentic Verification steps in right here. The agent reviews extraction results and helps process more transactions without manual intervention. The goal is to significantly increase the touchless rate while maintaining high processing quality. This creates a direct economic benefit: The more transactions that can be reliably processed in the background, the lower the manual workload. Agentic Verification is designed for use across industries and can be deployed in various extraction scenarios. The added value: more dark processing, less manual review, and greater flexibility.

Accounting

Auto Accounting – AI-Powered Account Assignment

Even after an invoice has been automatically captured, there are still tasks that require subject-matter expertise. Auto Accounting assists in the automated determination of appropriate general ledger accounts for incoming invoices. To do this, it uses the available invoice information to intelligently prepare the account assignment and further automate the subsequent purchase-to-pay process. The solution is designed to be industry-agnostic and can reduce manual steps even further, particularly when used in conjunction with automated invoice processing.

Response

Agentic Response – When the Process Asks on Its Own

Missing information, incomplete documentation, or unclear submissions lead to manual communication loops in many processes. This is exactly where Agentic Response comes in. The approach: If the AI detects that information is missing for further processing, an agent can prepare or initiate the necessary communication and feed the response back into the process. This creates a seamless cycle: Understand → Review → Identify missing information → Respond → Continue the process. This approach is particularly relevant for document-intensive processes in manufacturing, insurance, financial services, and business process outsourcing.

Agentic Verification

Agentic Verification – More Touchless Processing Agents

What happens if an extraction result isn’t clear enough for fully automated further processing?

Today, this often means manual verification.

This is exactly where Agentic Verification comes in.
The agent reviews extraction results and helps process more transactions without manual intervention. The goal is to significantly increase the touchless rate while maintaining high processing quality.

This creates a direct economic benefit: the more transactions that can be reliably processed in the background, the lower the manual effort required.

Agentic Verification is designed for use across industries and can be deployed in various extraction scenarios.

The added value:
More automated processing. Less manual verification. Greater flexibility than with traditional customization.
Auto Accounting
Agentic Response

From IDP to Agentic AI

For decades, Insiders has been synonymous with intelligent document processing and the automation of document-based business processes.

This experience forms the foundation for the next step in our development.
After all, successful AI agents need more than just a large language model. They need reliable information, an understanding of processes, integrations with existing systems, and clear guidelines.

That’s why we don’t view Agentic AI in isolation from existing business processes.

We combine IDP, AI, and process knowledge to create a new generation of intelligent automation.

Higher Touchless Rate

AI agents verify unreliable extraction results, thereby enabling more documents and processes to be processed further without manual intervention.

Less manual post-processing

Where traditional IDP processes hand off to humans when uncertainties arise, agents can perform additional checks and continue the process independently.

Dealing with Exceptions Intelligently

Missing information, incomplete documents, or unusual cases do not necessarily have to halt the process. Agents can assess the situation and take appropriate next steps.

Automatic Follow-ups When Information Is Missing

If a process is incomplete, AI agents can identify what is missing, initiate a targeted follow-up, and reassign the response to the correct process.

Less Rigid Customization

Instead of mapping every variation and exception through individual rules, AI agents enable more flexible decisions based on the specific document and process context.

From a Document to a Complete Process

IDP detects, classifies, and extracts. Agentic AI builds on this and enables further steps such as verification, validation, decision-making, and response.

The Next Step: Automating Processes Rather Than Individual AI Functions

For us, the real change brought about by Agentic AI does not lie in yet another AI model.
It lies in how AI functions interact with one another.

Classification, extraction, validation, completeness checks, communication, and other process steps can increasingly be linked to form intelligent workflows.

Document processing becomes process automation.

Implementing AI Agents in the Workplace

The journey into Agentic AI rarely begins with the technology. It begins with the question of which process currently requires the most manual intervention—and why.

In practice, processes that share three characteristics are well-suited: they involve high volumes, they are fundamentally rule-based, and they regularly encounter exceptions that currently require human intervention to resolve. Invoice processing is a typical example, as is the handling of applications and claims.

For productive use, AI agents need three things: a reliable understanding of incoming documents, defined boundaries for their own decisions, and a clear handoff point to a human. This is precisely where experience in document processing pays off—an agent is only as good as the data on which it bases its decisions.

The usual approach involves a defined subprocess with measurable results, such as the automated account assignment of incoming invoices. From there, the system can be expanded step by step.

An AI agent is a software system that processes information and, within defined parameters, can independently carry out tasks and trigger actions. In a business context, AI agents can, for example, review documents, verify information, or initiate further steps in a process.
Generative AI creates new content, such as text or summaries, based on input. Agentic AI goes a step further: It uses AI models and other tools to pursue a defined goal and carry out multiple steps to achieve it.
Intelligent Document Processing focuses on understanding documents, classifying them, and extracting relevant information. Agentic AI can build on this information and take on additional tasks within a business process.
Yes. When used in conjunction with Intelligent Document Processing, AI agents can utilize information from documents, verify results, and trigger further process steps depending on the specific use case.
Of particular interest are document- and communication-intensive processes involving many recurring decisions and manual intermediate steps—for example, in purchase-to-pay, insurance, financial services, manufacturing, or business process outsourcing.
It is common to start with a well-defined subprocess that handles a large volume of transactions and produces a measurable result—such as the account assignment of incoming invoices. This requires a reliable understanding of the incoming documents, as well as clearly defined boundaries within which the agent is allowed to make decisions on their own.
Rule-based automation requires a separate set of rules for each variant. An AI agent, on the other hand, makes decisions based on the specific process and can therefore handle cases that were not previously described. This significantly reduces the effort required for customization.

Agentic AI: AI Agents for Document-Based Processes

When AI Not Only Understands but Also Acts

Our AI Agents for Document-Based Processes

Agentic Verification – More Touchless Processing

Auto Accounting – AI-Powered Account Assignment

Agentic Response – When the Process Asks on Its Own

Agentic Verification

Auto Accounting