At 5M calls/year, routine tasks consumed agents. Voice AI now owns verification and scheduling; staff focus on the calls that need a human.
The largest telecommunications provider in the Netherlands, handling roughly five million customer service calls per year.
A traditional contact center model made it difficult to scale efficient service at that volume, with routine tasks like customer verification and...
“We wanted to make this next step toward the future. We see AI as a way to support more natural interaction with customers, while ensuring that human support remains available when it matters most.”
Also reported by
Telecommunications provider offering fixed and mobile services in the Netherlands.
Partnered with KPN to design, build, and scale its agentic AI customer service platform
KPN's Customer service calls is part of this use case:
Related implementations across industries and use cases
Basic bots struggled with nuanced, multi-system queries. Now, specialized AI agents execute transactions end-to-end for 9.5M customers.
Reps lost time hunting across complex systems. Now, AI agents surface verified answers and automate notes, freeing humans to connect.
Reps manually skimmed 12-page articles to resolve cases. Now, an AI assistant synthesizes live data to deliver answers in seconds.
Basic bots struggled with nuanced, multi-system queries. Now, specialized AI agents execute transactions end-to-end for 9.5M customers.
Reactive support for 15M broadband upgrades drove high call volumes. Now, AI agents proactively text and call to schedule installations.
Native ad tools optimized for platform metrics, limiting spend efficiency. An AI agent now adjusts live campaigns to meet business goals.
Duplicated effort and fragmented knowledge slowed 150+ app releases. 120+ AI assistants cut timelines 15% and lifted productivity 20–25%.
Data siloed across five products, no shared identity. A unified ID and AI trained on slang now complete cancellations inside the chat.
Agents summarized every call by hand and memorized talk scripts. Voice-to-text and real-time screen pops cut after-call work by 80%.
At 5M calls/year, routine tasks consumed agents. Voice AI now owns verification and scheduling; staff focus on the calls that need a human.
The largest telecommunications provider in the Netherlands, handling roughly five million customer service calls per year.
A traditional contact center model made it difficult to scale efficient service at that volume, with routine tasks like customer verification and...
“We wanted to make this next step toward the future. We see AI as a way to support more natural interaction with customers, while ensuring that human support remains available when it matters most.”
Also reported by
Telecommunications provider offering fixed and mobile services in the Netherlands.
Partnered with KPN to design, build, and scale its agentic AI customer service platform
KPN's Customer service calls is part of this use case:
Related implementations across industries and use cases
Basic bots struggled with nuanced, multi-system queries. Now, specialized AI agents execute transactions end-to-end for 9.5M customers.
Reps lost time hunting across complex systems. Now, AI agents surface verified answers and automate notes, freeing humans to connect.
Reps manually skimmed 12-page articles to resolve cases. Now, an AI assistant synthesizes live data to deliver answers in seconds.
Basic bots struggled with nuanced, multi-system queries. Now, specialized AI agents execute transactions end-to-end for 9.5M customers.
Reactive support for 15M broadband upgrades drove high call volumes. Now, AI agents proactively text and call to schedule installations.
Native ad tools optimized for platform metrics, limiting spend efficiency. An AI agent now adjusts live campaigns to meet business goals.
Duplicated effort and fragmented knowledge slowed 150+ app releases. 120+ AI assistants cut timelines 15% and lifted productivity 20–25%.
Data siloed across five products, no shared identity. A unified ID and AI trained on slang now complete cancellations inside the chat.
Agents summarized every call by hand and memorized talk scripts. Voice-to-text and real-time screen pops cut after-call work by 80%.