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Project Overview
A company running a real-time audio and video communication product wanted to add AI features its users were starting to expect: live captions, transcripts after every meeting and short summaries with decisions and action items.
ProsperaSoft integrated streaming speech recognition into the media pipeline, built a transcript service with speaker attribution, and used a language model to generate summaries, action items and searchable meeting notes.
Core Features
- Live Captions: streaming transcription shown to participants during the call
- Speaker Attribution: transcripts labelled by participant using the platform's audio tracks
- AI Summaries: summaries, decisions and action items generated when the meeting ends
- Meeting Search: transcripts indexed so users can search what was said across meetings
Client Challenges
- Real-Time Constraints: captions had to appear quickly without affecting call quality
- Scale: many concurrent meetings meant transcription had to scale up and down with usage
- Accuracy: domain terms, accents and cross-talk reduce recognition accuracy
- Privacy: users needed control over recording, transcripts and retention
Key Highlights
Live and Accessible:
- Streaming recognition with partial and final results
- Captions displayed per speaker in the client apps
Captions make meetings accessible as they happen.
Useful After the Call:
- Summaries, decisions and action items
- Shareable notes linked to the recording
Every meeting produces notes people actually read.
Built for Scale:
- Separate media and AI services
- Queues and autoscaling for summary generation
Transcription workers scale with meeting load.
Privacy by Design:
- Consent prompts and visible recording state
- Retention settings and deletion on request
Users and admins stay in control.
Adding AI to Real-Time Communication
Solution Highlights
Best Practices Integrated
Results & Benefits
- Media Integration: audio tapped from the WebRTC media server per participant track
- Speech Recognition: streaming speech-to-text with custom vocabulary for domain terms
- Language Model: summaries and action items generated from the full transcript with structured output
- Isolation: AI processing separated from the media path so calls stay stable
- Cost Control: transcription only when enabled, summaries generated once per meeting
- Security: encrypted storage and access limited to meeting participants
- Competitive Features: the product gained AI features users compare when choosing a meeting tool
- Accessibility: live captions help participants in noisy environments and with hearing impairments
- Productivity: users get meeting notes and action items without writing them
Solution Highlights
- Media Integration: audio tapped from the WebRTC media server per participant track
- Speech Recognition: streaming speech-to-text with custom vocabulary for domain terms
- Language Model: summaries and action items generated from the full transcript with structured output
Best Practices Integrated
- Isolation: AI processing separated from the media path so calls stay stable
- Cost Control: transcription only when enabled, summaries generated once per meeting
- Security: encrypted storage and access limited to meeting participants
Results & Benefits
- Competitive Features: the product gained AI features users compare when choosing a meeting tool
- Accessibility: live captions help participants in noisy environments and with hearing impairments
- Productivity: users get meeting notes and action items without writing them
Technology Stack:
The solution combines real-time media engineering with speech and language AI. Related services: AI integration, AI audio and video and AI knowledge search.
Per-participant audio tracks.
Streaming transcription.
Summaries and action items.
Real-time signalling and caption delivery.
Transcription and AI workers.
Transcript search.
Pub/sub for live captions.
Autoscaling AI services.
WebRTC Media Server:
Per-participant audio tracks.
Whisper / Cloud Speech APIs:
Streaming transcription.
OpenAI / Claude:
Summaries and action items.
Node.js:
Real-time signalling and caption delivery.
Python:
Transcription and AI workers.
Elasticsearch:
Transcript search.
Redis:
Pub/sub for live captions.
Kubernetes:
Autoscaling AI services.
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