Services

AI agents for appointment-based services

Keep enquiry coverage available while staff focus on the customer in front of them.

The customer context

Keep enquiry coverage available while staff focus on the customer in front of them.

Answer service questions and turn appointment enquiries into complete requests that the team can confirm.

What this workflow can cover

  • Explain services, requirements and working hours
  • Collect preferred time, contact and relevant details
  • Prepare or execute only the approved scheduling step
  • Hand unusual requests to reception with context

Services

How it works

  1. 1

    Define the services, information and confirmation boundary.

  2. 2

    Launch on the website or the channel customers already use.

  3. 3

    Review incomplete requests, handoffs and confirmed outcomes each week.

What your team gets

Fewer missed enquiries

Less interruption for service staff

More complete requests before confirmation

Telp

How your team keeps control

Industry copy is not a hidden rule engine

Your actual policies are configured as knowledge, typed fields and approved tools.

Start with a representative workflow

Pilot one journey across normal, incomplete and exceptional customer requests.

Keep ownership visible

The team can see which conversation, tool and person owns the next action.

FAQ

Frequently asked questions

Is AI agents for appointment-based services a separate Telp product?

No. It is a practical configuration pattern that combines Telp channels, knowledge, tools and handoff around a common industry workflow.

Do we need to replace our current systems?

Not necessarily. The first rollout can send structured outcomes to existing tools, then use a deeper approved integration where it adds clear value.

How do we validate the industry setup?

Test real examples, missing information, exceptions and human takeover with the team that owns the process before expanding the scope.

Want to validate this workflow with your own examples?

Tell us the channel, current process and first result you want to improve. We will suggest a focused rollout path and the cases your team should test.