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How Swisscom uses Rasa

50%

“Optimizing LLM usage reduced operational costs by 50%”

As published on rasa.com. Captured by usedby on Oct 8, 2026.

What happened

Swisscom rebuilt its customer service AI agent, Sam, on Rasa's CALM framework, integrating LLMs for natural multi-turn dialogue and zero-shot intent recognition. The agent handles a wider range of customer queries without human intervention and can access real-time customer information.

Summary written by usedby from the source page, in English. The figures are those of Rasa and Swisscom, not ours.

  • 1.6x“Writing conversation flows and validation became 1.6x faster.”
  • 20 weeks“Swisscom prototyped and deployed the first version of the new LLM-based Sam to production within 20 weeks by using Rasa's tools to quickly test and refine features.”

Optimizing LLM usage reduced operational costs by 50%, while automation freed human agents to focus on more complex tasks. Faster deployment cycles allowed Swisscom to adapt quickly to customer needs and business priorities.

From the page. rasa.com, captured Oct 8, 2026

Rasa was the perfect partner to bring our vision to life.

Rolf Neukom, Program Manager AI Service for B2C at Swisscom, Swisscom. Source, captured Oct 8, 2026

What the story claims, and what we checked

We compared the story with its live page on Oct 8, 2026.

  • The figure: 50%CheckedPrinted word for word on the page, near the name of Swisscom.
  • The passage quoted aboveCheckedCopied word for word from the page, near the name of Swisscom.
  • Swisscom uses RasaCheckedConfirmed line. Latest check across sources: Oct 8, 2026.
  • The result itselfNot checkedWe quote it; we did not measure it.

Same company, same tool or same industry.

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