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Thesis: Sovereign Voice AI for Sensitive Public-Sector Services

Knightec Group AB

Sammanfattning

This thesis position involves designing and implementing a modular Sovereign Voice AI prototype that utilizes locally deployable AI models for speech recognition, language processing, translation, and speech synthesis. The work will focus on real-time multilingual communication for public sector applications, ensuring data sovereignty and privacy. The role is based in Sundsvall, with a start date in January or March 2027, and is suitable for students graduating in June 2027.
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Det här erbjuder vi

Opportunity to work on cutting-edge technology in voice AI.Gain practical experience in a research prototype development.Collaborate with a leading strategic partner in product and digital service development.

De nordiska länderna

Ansök senast: Öppet tillsvidare
Publicerad: 2026-10-15

Beskrivning

High Level Description
Recent advances in speech recognition, generative AI, and speech synthesis have created new opportunities for voice-enabled services such as real-time translation, transcription, and conversational interfaces. However, organizations handling sensitive information, particularly within the public sector, face challenges when using cloud-based AI services due to privacy and data sovereignty requirements.

This thesis investigates whether locally hosted speech and language models can provide sufficient accuracy, performance, and reliability for real-time voice applications involving sensitive information. The goal is to develop and evaluate a reusable Sovereign Voice AI platform that processes audio and text entirely within infrastructure controlled by the organization.

Project Description
The student will design and implement a modular Sovereign Voice AI prototype using locally deployable AI models for speech recognition, language processing, translation, and speech synthesis. The system should expose reusable components through APIs, allowing it to support different applications.

The primary reference scenario will be real-time multilingual communication between citizens and public-sector employees, where conversations may contain sensitive information such as personal details, financial information, or housing circumstances. The prototype will be evaluated using synthetic conversations and volunteer participants rather than real citizen data.

A key focus will be developing mechanisms to identify potentially unreliable interpretations, particularly errors involving critical information such as names, numbers, dates, monetary amounts, and addresses. The system should investigate ways to highlight uncertainty and request clarification when necessary.

Different locally deployable models and hardware configurations will be compared in terms of transcription and translation accuracy, latency, resource requirements, and reliability. The resulting solution should provide reusable components, a reference application, and a benchmark for evaluating future voice AI models.


Who are we looking for?

  • Bachelor/Master of Science in Computer Science/Engineering
  • Graduation in June 2027
  • Fluency in Swedish, both written and spoken
  • Fluency in English, both written and spoken


Purpose
In this thesis, investigate the following questions:
  • Feasibility of locally hosted voice AI - To what extent can locally deployable speech and language models support real-time multilingual communication under realistic hardware constraints?
  • Performance and efficiency - What trade-offs exist between model size, computational requirements, latency, and output quality?
  • Accuracy and reliability - How do factors such as background noise, accents, speech rate, and specialized terminology affect transcription and translation accuracy?
  • Consequential errors - How reliably can the system preserve critical information such as names, numbers, dates, monetary amounts, and negations, and how can errors with significant consequences be identified?
  • Uncertainty and clarification - Can uncertainty-aware mechanisms identify potentially incorrect interpretations and request human confirmation to reduce consequential errors without unnecessarily slowing down conversations?
  • Data sovereignty - How can the system be designed to ensure that sensitive audio, transcripts, and generated information remain within infrastructure controlled by the organization?

  • The study will focus on existing locally deployable models rather than training new models from scratch. A reasonable scope is Swedish and two to three additional languages, using one reference application and a limited selection of models.

    The implementation is intended as a research prototype and reusable technical foundation rather than a production-ready solution.


    An Exciting Journey with Knightec Group
    Semcon and Knightec have joined forces as Knightec Group. Together, we are Northern Europe's leading strategic partner in product and digital service development. With a unique combination of cross-functional expertise and a holistic business understanding, we help our clients realize their strategies - from idea to complete solution.

    Practical Information
    This is a thesis position, located at our office in Sundsvall . Start date January or March 2027.

    Please submit your application as soon as possible, but no later than 2026-11-30 . If you have any questions, you are welcome to contact johanna.edstrom@knightec.se . Note that due to GDPR, we only accept applications through our careers page.

    Ansök till tjänsten

    Thesis: Sovereign Voice AI for Sensitive Public-Sector Services

    Denna arbetsplats har annonserats på Knightec Group SWE (former Semcon)-tjänsten den 2026-10-15 och publicerades av Knightec Group SWE (former Semcon).
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