Automation in context
The result connects to the next task in the workflow.
Service / AI solutions
AI within a real workflow.
Document classification, data queries, operations and business reporting. Purposeful AI with clearly defined operating boundaries.
AI solutions
Value starts with the use case.
We place AI in a specific task: assigning a document to a shipment, supporting a query or assisting operations. Production applications, prototypes and development work are presented separately.
Useful information
Data queries and reporting support everyday work.
Clear maturity levels
Production applications remain distinct from development work.
Two areas of expertise, connected to your task.
LLM-based solutions
We connect language models to existing software and business workflows so AI can deliver value as part of everyday work.
- LLM orchestration harnesses embedded in custom software
- Purpose-built agents for specific tasks
- MCP integration for existing software and data sources
Machine vision and document understanding
We turn images, video and documents into information that workflows can use: what is present, how it changes and what event it represents.
- Camera-based object detection and tracking
- Segmentation to separate individual objects in images
- Event recognition and evaluation
- Document classification and workflow integration
CAPABILITIES
What do we connect?
Document processing
In production: automated classification, shipment assignment and metadata comparison.
Natural language queries
In production: database queries supported by natural language questions.
AIOps and business reporting
Operational support and BI solutions running in production.
Knowledge-based answers
Prototype: a RAG approach connects answers with a body of knowledge.
WORKFLOW
How the process works
These steps illustrate the approach. Configuration and implementation are designed for the specific assignment.
Task and data
Identify the specific workflow step and available data.
Integrate and evaluate
Develop the solution within the workflow and assess its results.
Operate and handle exceptions
Establish how results are used and where human involvement is needed.
IN PRACTICE
A document, a shipment, a connection.
In the logistics system, AI automatically classifies documents, assigns them to shipments and compares metadata. People intervene where document processing gets stuck.
Related referenceGOOD TO KNOW
Frequently asked questions
Are all these applications in production?
No. Document sorting, natural language data queries, AIOps and BI operate in production. RAG is a prototype, while WebWaste computer vision is in development.
Does AI remove all human checks?
No. The logistics document workflow needs human intervention for exceptions. The review process for other use cases is defined individually.
Where should we start?
With a specific recurring task and a review of the available data. Discovery or a prototype can be commissioned independently.
NEXT STEP
Let’s discuss your next project.
A challenge to solve, a new idea or a system to improve. An initial outline is enough to start the conversation. The initial consultation is free of charge.