AZURE AI FOUNDRY
Azure AI Foundry for enterprise agents
We build agents and RAG on Azure AI Foundry with VNet, cost control, observability and enterprise deployment practices.
Azure AI Foundry for enterprise agents
An Azure AI Foundry rollout matters when you want the Azure Foundry perimeter, not a generic self-hosted agent. Before selecting tools, we define journeys, permissions, data and supervision criteria so the agent operates under your company's control.
We work from Barcelona and Madrid and remotely with teams across Spain, Europe, LATAM and the United States. The process combines discovery, access hardening, verifiable releases and operational documentation.
We hand over code, repositories, configurations, skills and documentation in accounts owned by your company. You can audit, rotate credentials or change supplier without lock-in.
We build agents and RAG on Azure AI Foundry with VNet, cost control, observability and enterprise deployment practices. That is why we prioritise a governable, measurable agent ready to evolve without rebuilding its foundations.
THE STARTING POINT
The challenges around Azure AI Foundry
The value of Azure AI Foundry depends on a design that serves operations and governance, not only a demonstration.
Scope is too vague
When the Azure pilot lacks network, cost and observability controls, the project fills with exceptions and operational risk. Agreeing the priority journey stops us building the right solution for the wrong problem.
Permissions and secrets lack governance
Without defined accounts, secrets and least privilege, the agent is either exposed or blocked. We design auditable access from the first deployment.
No evolution criteria
A first release with no metrics or accountable owner soon stalls. We leave traceability so improvements can be prioritised with evidence.
HOW WE WORK
From need to running agents on Azure
We sequence technical and governance decisions so the first release is useful and maintainable.
Understand operations
We map users, data, channels and constraints to define how Azure AI Foundry must fit daily work.
Design limits and handoffs
We validate what the agent may do alone, when it escalates to people and which systems are the source of record.
Build and integrate
We connect official APIs, configure skills/workflows and test the highest-impact cases with controls.
Release and measure
We put the solution into operation, measure the outcome and prioritise the next improvement for running agents on Azure.
WHAT YOU GET
What Azure AI Foundry leaves ready
We deliver an operational foundation your team can govern, measure and continue to evolve.
Working agent or operation
Azure AI Foundry ready for the agreed journeys and reviewed before wider adoption.
Integrations and permissions
Connections, systems of record, secrets and limits documented so operations do not rely on informal knowledge.
Code and configuration
Repositories, skills and configuration under your company's control, transferable to another team.
Evolution plan
Metrics, accountable owners and a prioritised backlog after the first release.
EXPERIENCE
Technology applied with governance
We deploy Foundry with VNet, cost control and enterprise observability.
- Scope, assumptions and risks visible before the deployment is committed.
- Least privilege, secrets and systems of record defined from the design stage.
- A measurable first release before expanding channels or departments.
- Code, configuration and documentation under your company's control.
FAQ
Questions about Azure AI Foundry agents
Have a project in mind?
Tell us what you need around Azure AI Foundry agents. We will help you turn it into a clear, viable delivery plan.