AI System Development · Integration · Internal Tools

From pilot projects and process knowledge, productive internal AI systems are created.

Trixner digital solutions develops custom applications that integrate company knowledge, automation, and AI components into real workflows.

InterfaceLine-of-Business System

Sources, status, approvals, and AI answers in one interface.

DataSources

Documents, CRM, API

LogicWorkflows

Rules, AI, Handover

When is it a good idea?

When standard tools don't map the process cleanly.

Many companies work with Excel, email, forms, and specialized systems that don't interact well. A custom AI application can pick up right where they leave off: capturing data, retrieving knowledge, preparing processes, and supporting decisions.

The focus is on stable internal systems, not on short-term demos.

Build

Internal applications

Tools for billing, auditing, reporting, documentation, or specific business processes.

Integrate

Connecting Systems

Merge CRM, data sources, documents, forms, and existing workflows.

Operate

Prepare for Operation

Take into account roles, monitoring, limits, documentation, and extensibility.

System Types

AI system development combines product thinking with process understanding.

Depending on the goal, a RAG interface, a workflow tool, an auditing assistant, a reporting system, or an agent-like task pipeline with human approval is created.

Knowledge
RAG Interface

Find knowledge, display sources, and make answers usable in a controlled manner.

Workflow
Process tool

Structure processes, maintain status, and prepare handovers.

Assist
AI Assistant

Review documents, summarize content, and create decision-making bases.

Process

From domain logic to a stable application.

01

System Concept

Define users, data, processes, roles, and technical limitations.

02

Prototype

Build a first usable version with core features and real data.

03

Integration

Stabilize interfaces, permissions, workflows, and handovers.

04

Further development

Systematically incorporate feedback, monitoring, and new requirements.

Next step

Let's check if a custom AI application makes sense.

In the initial consultation, we clarify the process, user groups, data sources, and a realistic first version.