Customer Service Automation
The Norwegian Red Cross needed a lower-cost, privacy-preserving way to support sensitive multilingual conversations for vulnerable groups when human interpreters were expensive or unavailable.
Reported impact
The Norwegian Red Cross expanded access to interpretation for vulnerable groups, cut translation costs substantially, and created a secure operational model that can also serve public-sector environments with strict data-handling requirements.
In collaboration with the Norwegian Red Cross, Capgemini developed and hardened BabelSpeak as a secure AI interpretation service for sensitive multilingual conversations. The system supports speech-to-speech, speech-to-text, text-to-text, and text-to-speech translation across about 100 languages, making it useful where live interpreters are expensive or hard to arrange. Capgemini and the Red Cross ran extensive testing with native-language reviewers to measure translation quality, expose weaknesses such as dialect handling, and iteratively refine the models. The team also brought in Telenor's AI Factory so processing and data handling could remain under Norwegian control, which is critical for sectors such as police, healthcare, municipalities, and the military. Conversations and text are routed through BabelSpeak, translated or transcribed in real time, and returned in a private workflow that reduces cost while broadening access to help for refugees and formerly incarcerated people.
Speech or text from a sensitive conversation is sent to BabelSpeak, translated or transcribed across speech and text modes, processed within Norway through Telenor AI Factory controls, and returned to the participants in real time.
"BabelSpeak translates between 100 different languages in four ways: speech to speech, text to text, speech to text, and text to speech."
"Cost of interpretation reduced up to 90%"
"Red Cross engaged Capgemini to build BabelSpeak, a tool for real-time translation and transcription in approximately 100 languages"
"Telenor's recently established AI Factory becoming a key partner to ensure the entire solution was under Norwegian control."
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
The page JSON-LD lists numberOfEmployees value 1072 for Norwegian Red Cross; the standard mapping classifies 1,000+ employees as Enterprise.
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