CUSTOMER SERVICE

AI agents for customer service

We automate the first line of support with context, human handoff and logging in your service systems.

AI agents for customer service

A customer-service AI agent matters when you need omnichannel support agents with operations and CRM, not only a one-page bot. 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 automate the first line of support with context, human handoff and logging in your service systems. That is why we prioritise a governable, measurable agent ready to evolve without rebuilding its foundations.

THE STARTING POINT

The challenges around a customer-service agent

The value of a customer-service agent depends on a design that serves operations and governance, not only a demonstration.

  • Scope is too vague

    When support saturates and leaves no CRM context, 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 serving with traceability

We sequence technical and governance decisions so the first release is useful and maintainable.

  1. Understand operations

    We map users, data, channels and constraints to define how a customer-service agent must fit daily work.

  2. 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.

  3. Build and integrate

    We connect official APIs, configure skills/workflows and test the highest-impact cases with controls.

  4. Release and measure

    We put the solution into operation, measure the outcome and prioritise the next improvement for serving with traceability.

WHAT YOU GET

What a customer-service agent leaves ready

We deliver an operational foundation your team can govern, measure and continue to evolve.

  • Working agent or operation

    a customer-service agent 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 integrate support with CRM, human handoff and resolution metrics.

  • 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 AI agents for customer service

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Tell us what you need around AI agents for customer service. We will help you turn it into a clear, viable delivery plan.