Real-time Multilingual Speech-to-Text Platform

We developed a real-time speech-to-text platform for a UK-based client operating across multiple EU markets, where conversations naturally switch between languages and accents. The system listens to live audio streams, transcribes speech with low latency and automatically enriches each transcript with structured metadata such as speakers, languages, topics and key entities.

Instead of manually reviewing recordings or relying on generic, single-language tools, the client now has a tailored ASR solution that respects their regulatory requirements, integrates with existing systems and adapts to the vocabulary of their domain.

This platform forms the backbone for downstream use cases such as live monitoring, compliance checks, call and meeting analytics, customer insight dashboards and GenAI assistants that can work directly on high-quality multilingual transcripts.

What this solves

For organisations working across Europe, spoken data is one of the richest but most underused sources of information. Calls, meetings, support conversations and training sessions are often recorded but rarely analysed, partly because languages, accents and code-switching make transcription difficult. Manually processing audio is slow, expensive and inconsistent, and off-the-shelf tools often fail on domain-specific terminology or provide transcripts that are hard to search and reuse.

Our platform solves this by providing accurate, low-latency transcription for multiple European languages and English in the same stream, with automatic language detection and speaker diarisation. Every transcript is enhanced with timestamps, detected topics, named entities and sentiment cues, making it easy to search, filter and connect spoken content to other data sources. The result is a single, searchable layer of conversational data that teams can trust and build on.

How we did it

We designed the solution as a streaming ASR pipeline that ingests audio from telephony systems, meeting tools and web applications, processes it in near real time and delivers structured outputs through APIs and event streams. A multilingual speech recognition engine handles language detection and transcription, while additional components perform speaker segmentation, punctuation restoration and quality checks.

On top of raw transcripts we run metadata extraction services: keyword and topic detection, named entity recognition, language tags, confidence scores and conversation-level summaries. All outputs are stored in a way that supports both analytics and GenAI workloads – from time-aligned transcripts for dashboards to segment-level chunks optimised for retrieval-augmented generation. Security, encryption and access control are handled end-to-end to meet EU data protection expectations and the client’s internal compliance policies.