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A chatbot answers questions. An AI agent gets work done: it reads documents, reconciles data, prepares decisions and writes results to ERP and CRM - with clear permissions, approval steps and a complete audit trail.
02 - Agent types
Six agent types proven in practice - each with input data, connected systems, a review step and one metric the agent is measured against.
The agent reads tender documents, extracts the requirements, matches them against your product data and drafts a proposal. Requirements you do not cover are flagged and presented to sales for review.
The agent understands incoming requests, answers standard cases itself - based on your manuals, orders and history - and hands over special cases with full context and a suggested reply to the right person. Every reply is documented in the CRM.
Invoices, delivery notes, order confirmations: the agent reads incoming documents, extracts line items and amounts, checks plausibility and hands over structured data to the ERP. If a document falls below the confidence threshold, it goes to a human with full context - that is the architecture behind our product robodocxs.
The agent answers internal questions from manuals, contracts, meeting minutes and file repositories - always citing its sources, so every answer stays verifiable. It respects existing permissions: everyone only sees what they are allowed to see anyway.
The agent finds duplicates, fills in mandatory fields and enriches product and customer data according to your rules - across ERP, CRM and PIM. It never makes silent changes: it submits them as proposals for approval until you grant it more autonomy.
Orders arrive by email, fax PDF or portal - the agent detects line items, maps customer prices, checks plausibility and creates the order in the ERP. For amounts or deviations above your thresholds, it requests approval.
Figures in the examples are illustrative process values; values relating to robodocxs are example values from production robodocxs operations and depend on document quality and process.
03 - Integration
The difference between a chat interface and a real agent is integration: access, permissions, logging and approvals become part of the architecture - tailored to your system landscape and your data protection requirements.
04 - How your agent is built
No research project: we develop along a clear process, on real cases, with approval steps - until the agent carries its weight in everyday operations.
Which task does the agent take over, and how is it measured? Metric and boundaries are fixed before anything is built.
Knowledge sources, access, interfaces and the permissions concept are assessed.
Tools, knowledge connection, rules and minimal rights - cleanly scoped within your system landscape.
Historical and current cases: accuracy and edge cases are measured before the agent is allowed to execute anything.
In production, but safeguarded: only once quality is proven does the agent get more autonomy.
Metrics, logs, new cases: the agent is continuously monitored and further developed.
05 - From the field
Our own product robodocxs is an AI agent for document processing - in production at companies for years. It is also our reference architecture: the same principles of knowledge connection, confidence thresholds, approvals and logging go into every agent we build.
reads invoices, delivery notes and order confirmations from email, PDF and scan
extracts line items, amounts and suppliers and reconciles them with existing data
hands over structured data to ERP, accounting and DMS
over 80 % of documents without manual intervention - example value from production robodocxs operations, depending on document quality
below the confidence threshold, a document goes to a human with full context
every processing step logged - traceable down to the source document
06 - What is an AI agent
An AI agent is a software solution that processes information from your company data, prepares decisions within defined rules and executes actions in connected systems. Unlike a plain chatbot, an agent can review documents, update data in the ERP or route tasks to employees. To do this, it combines three building blocks: knowledge sources (your documents, master data and history), tools (access to ERP, CRM, email and file repositories) and rules (what it may do, what it submits for approval, what it logs).
Answers questions in dialogue - often with general knowledge, without access to your systems. It informs, but it gets nothing done.
Supports employees on demand: summarizes, drafts, researches. A human initiates every single task.
Works through a process autonomously: reads inputs, makes preliminary decisions, executes actions in your systems - within clear boundaries and with review steps.
Follows fixed rules and needs structured data. Strong for clear-cut processes - the agent complements it wherever emails, PDFs and free text need to be understood.
07 - FAQ
That depends on the task, your system landscape and the review requirements. We start with a clearly scoped first agent including a business case: before implementation you see exactly which savings offset which effort, and you decide based on the numbers.
We typically deliver a first production agent within a few weeks: analysis, a prototype tested on real cases, then a pilot phase with approval steps. The exact timeline depends mainly on system access and data availability - we clarify that during the analysis phase.
The data of the process it takes over: incoming documents, master data, case history, manuals or price lists. The agent only gets access to what it needs for its task - no stockpiling of data.
Yes. Depending on your requirements, we run agents in your infrastructure, in an EU cloud or managed by us. The choice of model also follows your requirements for data protection, quality and cost.
The agent draws primarily on approved company data and defined sources. Uncertain or contradictory results are detected via confidence thresholds and handed over for review. The agent never executes critical actions without approval - and every action is logged.
Yes - that is the core of our work. We connect common ERP and CRM systems as well as custom line-of-business applications: via API, through databases or, where no interface exists, through robust import/export and document processes.
When a task is recurring, has meaningful volume and its inputs are unstructured - such as emails, documents or free text. If the process is fully structured and rule-based, classic automation is often the more economical solution. That is exactly what we verify before implementation.
Yes, if your requirements demand it: EU hosting, operation within your own systems and data processing agreements are part of the architecture decision - we plan data protection in from the start, not as an afterthought.
With a free initial consultation: we clarify the task, your system landscape and the use case with the greatest leverage. A short analysis phase with a business case follows - you decide based on the numbers whether and where to start.
08 - Related services
In an initial consultation we find the agent with the greatest leverage - no strings attached, concrete, based on the numbers.
