Add-on
AI is attached to old processes
Individual tools optimize tasks, but value creation remains unchanged.
- isolated prompts and automations
- data remains in silos
- knowledge does not flow back
- productivity rises only in isolated areas
/ 00·FLAGSHIP FOR AI-NATIVE BUSINESS MODELS
AI-native Consulting
Rethink AI. Rebuild business models.
We develop business and organisational models from the possibilities of AI. To do so, we combine strategic consulting with building knowledge systems, agents and applications. Our goal: enable new value creation and give people more room for learning, decisions and collaboration.
01Consulting + product studio + AI system architecture
02RAG, Knowledge Graph, agents, workflows, interfaces
03From business model to productive operations
/ 01·ADD-ON VS. AI-native
AI as an add-on remains piecemeal.
The leap does not happen when AI accelerates isolated tasks. It happens when the business model, knowledge, agents, and operations are designed together.
AI-native
The business model is built AI-native
Knowledge, agents, workflows, and interfaces form productive enterprise intelligence.
- RAG and Knowledge Graph as memory
- agents orchestrate real work
- operations and learning are connected
- new offerings and scaling become possible
/ 02·OPERATING MODEL
Designing business model, organisation and AI system together.
It starts with the question of what contribution an organisation wants to make and for whom it wants to create value. From this we develop offerings, roles, ways of working and the right technical architecture – and clarify which decisions people make, which tasks AI can take on and how results are reviewed.
- AI-native
Business and organisational model
Design new offerings and forms of value creation – and align roles, responsibility and collaboration with the new possibilities.
Value creation, roles and responsibility - AI-native
AI System
Connect knowledge, agents and applications into a transparent architecture: RAG, knowledge graph, workflows and interfaces.
System intelligence instead of individual tools - AI-native
Operation and further development
Review systems in use, learn from experience and improve them in a targeted way.
Review, learn, improve
/ 03·MULTI-AGENT SYSTEM
Agents with clear tasks and boundaries.
Specialised AI agents make information accessible, prepare analyses and carry out defined work steps. We deliberately define their tasks and scope of action: people set goals, review results and are responsible for decisions. Which steps run independently and where approval is required depends on the use case.
Orchestrator
Coordinates the agents and distributes tasks within a defined framework.
Researcher
Searches data sources and gathers relevant information.
Analyst
Analyzes data, identifies patterns, and delivers insights.
Strategist
Prepares recommendations as a basis for human decisions.
Executor
Carries out approved work steps and automates workflows.
Monitor
Monitors results and reports anomalies to the people responsible.
Active Agent
Orchestrator
Coordinates the agents and distributes tasks within a defined framework.
/ 04·ENTERPRISE INTELLIGENCE
The new intelligence layer of the enterprise.
RAG system, multimodal Knowledge Base, Knowledge Graph, agents, Workflows, and Interfaces do not work side by side. They are connected into a productive architecture.
RAG System
Sources, context, and answers are connected in a traceable way.
Knowledge Graph
Relationships, terms, and meanings become explicitly usable.
Agent Orchestration
Specialized roles handle research, analysis, implementation, and control.
Workflows & Tasks
Strategy is translated into operational steps, responsibilities, and decisions.
SaaS, Voice & Cockpit
People control the system through high-quality, productive Interfaces.
Learning Loop
Results, reflections, and corrections flow back into knowledge.
/ 05·POSITIONING
Consulting + product studio + AI systems architecture.
AI-native Consulting combines strategic business model work with in-house product development and resilient AI systems architecture.
01
Strategic consulting
We translate AI into business model logic, priorities, and management decisions.
02
Product studio
We build our own SaaS and AI products and know production operations from the inside.
03
AI systems architecture
We connect Best-of-Breed tools into a Stack that carries knowledge, agents, and Interfaces.
Not an agency. Not a tool integrator. Not slideware consulting.
/ 06·RESPONSIBILITY
Powerful AI needs responsible design.
AI can support research, analysis and recurring work. Which goals we pursue with it and how we use the time gained remains a human and organisational decision.
That is why we consider capability, attitude, culture and incentives together with the design of work. The aim is to create room to act that supports people in thinking and acting and helps organisations develop.
For every system we clarify
- Tasks and boundaries
- Access rights and approvals
- Review of results and responsibility
The person behind the work
Dr. André Salfeld
Founder and consultant
As a lecturer, AI architect and author, I connect the development of people and organisations with practical systems design. My conviction: for the leap in intelligence brought by AI to become an evolutionary leap, we must act in a highly intelligent and highly conscious way.
Highly intelligent, for me, means using the new possibilities of people and AI working together. Highly conscious means examining motives, including perspectives and taking responsibility for the consequences.
Get to know my profile and approach/ 07·ENTRY POINT
From first conversation to AI-native potential analysis.
The entry remains low-threshold, but the professional start is a clear premium audit with outcome, roadmap, and management briefing.
First Conversation
We clarify the starting point, ambition, and strategic levers.
Potential Analysis
We assess where AI can structurally change your business model.
Architecture Sprint
We design the right AI stack from knowledge, agents, Workflows, and Interfaces.
Implementation
We build the productive components iteratively and measurably.
Operations & Learning
We move the system into operations and continue developing it.
/ 08·WORK EXAMPLES
Work examples in development.
We show work examples as soon as they are accessible and agreed. Until then, we describe the verifiable interim status – without figures we cannot yet substantiate.
In development
E-V-A: reflection and knowledge work
For the association Ethik und Verantwortung in der Arbeitswelt, a knowledge base and conversational assistance are being built that connect reflection, knowledge work and technical support. André Salfeld chairs the association.
Next checkpoint
A publicly accessible example with clearly named roles.
In development
Industry project
An independent venture in a regulated industry is being built as an AI-native product and knowledge architecture. Until an agreed presentation is available, we show it anonymised.
Next checkpoint
Agreed description of our own contribution.
In use
Our own knowledge and agent architecture
A knowledge base, agents with defined tasks, project management and voice interfaces work together in our own daily work – with clarified approvals and responsibilities.
Next checkpoint
A documented workflow that others can follow.
/ 09·CONTACT
Ready to build your business model AI-native?
Start with a first conversation. It can lead into an AI-native potential analysis with roadmap, architecture, and management briefing.
Email: info@ai-native-consulting.com
Location: Münster, Germany