You know AI matters, but not where to begin
Start with consulting and process assessment to find the first workflow worth improving.
DiscoveryPrioritization
AI implementation for business processes
AI implementation for business processes.
Gavenir helps companies identify AI opportunities, design AI-supported workflows, and implement working AI solutions for daily operations.
We work where business processes, ERP systems, documents, teams, approvals, data, and IT implementation meet. The starting point is not a generic AI tool. It is the workflow: what repeats, where work gets stuck, which systems are involved, who needs to review the result, and what output the business actually needs.
AI implementation at Gavenir means turning a specific business-process opportunity into a controlled workflow solution that people can use in daily operations.
Where projects start
Different starting points, one implementation path
Some companies arrive with a clear process. Others have AI interest but no scoped use case yet. The service path is built to move both situations toward a practical first implementation.
A repeated process already slows teams down
Move directly into workflow mapping, automation design, and a focused pilot around that process.
WorkflowPilot
A prototype exists, but it is not production-ready
Clarify governance, integration, review logic, access, hosting, and the path into daily operations.
GovernanceIntegration
Local implementation focus
A Liechtenstein-based partner for practical AI implementation
Many companies are interested in AI, but the difficult part is turning interest into something useful inside daily work.
Gavenir is based in Liechtenstein and works with companies in Liechtenstein, Switzerland, and selected regional or international markets. The focus is practical AI implementation for business processes: identifying the right use case, designing the workflow, building a focused solution, and supporting the path toward productive use.
Many AI discussions start with a model, a tool, or a workshop. That can be useful, but it is rarely enough. Operational value appears when the process is clear: what repeats, where manual effort is high, which documents or data sources are involved, which systems need to receive or provide information, who reviews the result, and what AI should prepare, support, structure, or automate. Without those answers, the use case stays abstract. With them, the implementation path becomes much clearer.
Implementation scope
AI-supported workflows for business operations
AI opportunity and process assessment
Identify useful AI opportunities, separate realistic use cases from generic ideas, and understand the process, systems, data, people, and constraints involved.
AI process and solution design
Define the workflow, required inputs and outputs, review steps, ownership, system handovers, and implementation approach before development starts.
AI Agent prototypes and pilots
Build focused prototypes for one bounded process, test feasibility, and create evidence for internal alignment, budget, IT review, and next steps.
Implementation and integration
Move from prototype to operational use with the right level of integration, access control, review, hosting, governance, and ongoing improvement.
Implementation workstreams
AI implementation needs more than a model choice
The work combines process, software, data, governance, and operational adoption. This is the difference between an AI demo and a workflow that people can use.
Process and handover design
Map tasks, owners, input documents, decisions, approvals, and outputs so the AI-supported workflow has a defined operating context.
Documents and structured information
Clarify what the workflow reads, extracts, compares, prepares, stores, and sends into the next process step.
Software layer or focused prototype
Build the smallest useful workflow layer around the selected process instead of forcing a broad tool rollout.
Review, access, and improvement
Define human review points, permissions, system access, hosting, monitoring, and the improvement loop before productive use.
Where AI can help
Good candidates depend on repeated operational work
Gavenir is a good fit when a company has recurring work that depends on documents, data preparation, reviews, approvals, or system handovers.
Procurement workflows
Supplier quotes, purchase requisitions, ERP-ready output preparation, and process handovers.
Document-heavy reviews
Document checks, comparison, structured extraction, archives, and internal knowledge access.
Decision preparation
Internal approvals, onboarding reviews, operational data preparation, and handovers between teams.
How the first project starts
A practical path from AI idea to working solution
Clarify one process opportunity
Start with the workflow where repeated effort, documents, or handovers create visible friction.
Assess fit and constraints
Clarify data, systems, review steps, ownership, risks, and realistic AI support.
Design and build the workflow
Define inputs, outputs, boundaries, review logic, and a focused pilot or software layer.
Implement, govern, improve
Move toward productive use with integration, access control, hosting, monitoring, and continuous improvement.
Proof and governance
Senior implementation experience, clear process boundaries
Gavenir has delivered consulting and software projects for customers and brings senior experience in business processes, supply chain, procurement, software architecture, and AI implementation.
2021 Product solutions since 2021.
70 Locations across transformation work and international business teams.
500+ Professionals supported through standardized digital procurement processes.
16 ERP systems in data and process platforms, including SAP and Microsoft Dynamics.
20+ Rollouts, go-lives, and SAP integrations from process design through implementation.
Related service paths
Connect the implementation anchor to the right service paths
AI Consulting
Clarify the opportunity first
Use consulting when the process, scope, or first use case is not yet clear.
AI AutomationImprove recurring handovers
Use automation when documents, approvals, data preparation, or system handovers slow the workflow.
AI AgentsBuild controlled workflow assistants
Use agents when a bounded process can benefit from reading, structuring, preparing, routing, or selected execution.
FAQ
Common questions about AI implementation
What does AI implementation mean at Gavenir?
AI implementation means turning an AI opportunity into a working process solution. Gavenir helps clarify the process, design the workflow, build or configure the AI-supported solution, and support implementation into daily operations.
Is Gavenir an AI consulting company or an implementation partner?
Gavenir can provide AI consulting, but the goal is not advice for its own sake. The work is designed to lead toward process clarity, solution design, prototype, implementation, integration, or ongoing improvement.
Does Gavenir work with companies in Liechtenstein?
Yes. Gavenir is based in Liechtenstein and works with companies in Liechtenstein, Switzerland, and selected regional or international markets.
Do AI projects need full ERP integration from the start?
No. Many useful projects can start with a limited workflow, document handling, structured outputs, and human review. Deeper integration can be added when the process, governance, and business value are clear.
Can Gavenir build AI Agents?
Yes. AI Agents are one implementation path when a workflow is ready for agent-based support. Gavenir frames agents as controlled workflow components with review steps, permissions, and defined process boundaries.
What should we prepare before the first discussion?
Bring one process where work repeats, documents move between people or systems, approvals take time, or outputs need to be prepared manually. A perfect specification is not required.
How does Gavenir decide whether to use automation or an AI Agent?
The workflow decides. Some processes need document automation or a software layer. Others benefit from a controlled AI Agent. Gavenir starts from the process outcome and chooses the mechanism after inputs, review steps, and system boundaries are clear.
Ready to explore where AI can help?
If your team spends time reading documents, preparing data, checking information, coordinating reviews, or moving work between systems, Gavenir can help you assess where AI could create value and what a realistic implementation could look like.