Sovereign AI infrastructure — 4–6x more transcription per GPU

Built within our long-term engagement on a European video-consultation platform used by financial institutions, where European data-protection law makes third-party cloud AI APIs problematic: customer conversations cannot simply be shipped to external providers.

The mandate: production AI — speech recognition, translation, text-to-speech, vision — self-hosted, GDPR-compliant, on dedicated hardware, and economical enough to compete with cloud APIs.

• Stand up a complete self-hosted AI stack covering live multilingual transcription and translation in 15 languages (including Indian languages), speech synthesis and vision.
• Make the economics work: at the initial baseline, a GPU sustained only 4–6 concurrent live transcription streams — far too few to serve a real user base per unit of hardware.
• Operate it like production infrastructure: monitored, deployable, maintainable.

• Model stack selection and integration: Whisper (ASR) · MADLAD (translation) · a modern open-source neural TTS engine · an open vision-language model — all open models that can run entirely on infrastructure under the operator's control, re-evaluated as the open-model landscape moves.
• Dedicated GPU infrastructure: deployment on dedicated GPU hardware, containerized, with CI/CD and monitoring covering both service health and GPU utilization.
• Systematic concurrency engineering: structured benchmarking campaigns across model variants, precision settings, batching strategies and serving configurations — measuring real concurrent-stream capacity at acceptable latency and quality, not synthetic throughput.
• Vision in the loop: the same infrastructure hosts our vision-language-model-based damage analysis for insurance video calls, demonstrating that the stack extends beyond speech.

• up to 6× live-transcription capacity per GPU, up from the original baseline — a 4–6x capacity improvement on the same class of hardware, transforming the cost-per-stream economics of self-hosting.
• Full data sovereignty: audio, text and video processed exclusively on dedicated, controlled infrastructure — no third-party AI APIs in the data path; GDPR compliance by architecture.
• 15-language live captioning/translation (including Indian languages) running in a production video-consultation context.
• A reusable pattern directly applicable to data-residency-sensitive deployments — including Indian public-sector requirements for sovereign AI.