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AI Agent Engineering

AI agents that execute tasks. Not just answer questions.

We build specialized AI agents that live inside your business processes — and do real work there.

The Problem

The world has enough chatbots. What's missing are AI systems that actually take over work. Not demo toys that impress at conferences. Agents that review documents every day, reconcile data, prepare decisions, and move processes forward. The difference between a chatbot and an AI agent? The chatbot waits for your question. The agent works on your task. We build the second kind.

Our Solution

Our AI agents aren't generic tools that are good at everything and great at nothing. Each agent is developed, tested, and optimized for a specific business process. It knows the context, understands the data, and knows when to bring in a human. Technically, we use modern agent frameworks with tool-use patterns: the agent can access defined tools — databases, APIs, documents — and combines them to solve complex tasks. Via the Model Context Protocol (MCP), we connect agents to your system landscape. And via Enterprise BPM, we orchestrate the overall process with human-in-the-loop checkpoints.

agent-orchestrator
$ wildcard agent run --workflow claims-processing
[INFO] Initializing AI Agent Pipeline...
[INFO] Loading workflow: claims-processing
[OK] Connected to MCP Server (enterprise-connector)
[OK] Document extraction complete (3 files)
[HITL] Awaiting human approval for claim #4521...
[OK] Approval received from reviewer@company.de
[OK] Claim processed successfully
$ _

Typical Use Cases

Document Review & Classification

Incoming documents — invoices, contracts, applications — are automatically recognized, classified, and their relevant data extracted. The agent validates against master data and escalates discrepancies.

Email Triage & Response Suggestions

Incoming customer requests are analyzed, categorized, and paired with response suggestions. Routine cases are handled autonomously — complex cases are routed to the right team member.

Data Research & Decision Preparation

The agent researches internal and external sources, structures the information, and delivers a decision-ready briefing — including a recommendation and confidence score.

Proposal & Contract Generation

Based on customer data, product catalogs, and business rules, the agent drafts proposals or contracts — ready for human approval.

Multi-Agent Systems

For complex tasks, we deploy multiple specialized agents that collaborate: one researches, one validates, one produces the document. All orchestrated via Enterprise BPM.

Technology

We work model-agnostic. Depending on requirements, we use Claude (Anthropic), GPT-4 (OpenAI), or open-source models for on-premise deployments. Our agent frameworks are based on LangChain, LangGraph, and proprietary developments. Connection to enterprise systems happens via MCP servers, REST APIs, and where needed, RPA for legacy systems.

Claude
GPT-4
LangChain
LangGraph
MCP
Enterprise BPM
REST APIs

How We Work

1

Process Analysis

We understand your process in detail — not from the presentation, but from reality. Exceptions, edge cases, bottlenecks.

2

Agent Design

We define what the agent handles, which tools it needs, and where humans step in.

3

Development & Integration

The agent is built, connected to your systems, and embedded in the Enterprise BPM workflow.

4

Testing & Iteration

Intensive testing with real data. Multiple iteration rounds until quality is where it needs to be.

5

Go-Live & Monitoring

Production deployment with continuous monitoring, quality control, and ongoing improvement.

Ready for the next step?

Let's discuss your requirements — no commitment, concrete results.