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 AI-Native Application Development

AI-Native Video Conferencing & Live Streaming Development

We engineer custom, production-grade video conferencing and broadcast-quality live streaming applications with AI woven into every layer of the media pipeline. Your brand, your infrastructure, your data — not another vendor’s SaaS.

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Core AI Capabilities
  • Real-time AI noise suppression & echo cancellation
  • Live closed captions & multi-language subtitles
  • Intelligent speaker spotlight & active-speaker detection
  • Background blur via ML segmentation models
  • HLS adaptive bitrate streaming (up to 4K)
  • AI-powered recording with chapter markers & search
  • Auto simulcast & VP9/AV1 SVC quality adaptation

How It Works

Requirements & Architecture Design

We map your use case, compliance needs, and scale requirements to a custom SFU cluster design — choosing the right media server, codec strategy, and cloud/on-prem topology.

Core Platform Build

We develop the signalling layer, media server cluster, React/React Native SDK, and AI feature pipeline — noise suppression, captions, speaker detection, recording — in parallel sprints.

QoS, Observability & Handover

We wire up Prometheus, Grafana, and TimescaleDB for real-time quality monitoring, run load tests, then deliver full documentation and deployment runbooks.

What We Build

Custom SFU Architecture

Horizontally scaled media server cluster with gRPC + Redis for inter-server room routing. Scales from 10 to 10,000+ concurrent sessions without architecture changes.

Broadcast Live Streaming

WebRTC → HLS/DASH pipeline using FFmpeg. WHIP/WHEP support for OBS and hardware encoders. CDN-ready output for global audiences at up to 4K.

AI Meeting Intelligence

Speaker diarization, topic segmentation, and engagement scoring powered by LLM post-processing on Deepgram transcripts — delivered as structured JSON.

E2E Encryption & Compliance

DTLS-SRTP media encryption, RBAC, audit logging — GDPR, HIPAA, and PCI-DSS compliant architectures as standard.

Cross-Platform SDKs

JavaScript and React Native SDKs with full Safari/Chrome/Firefox support. C++ SDK for embedded and IoT endpoints.

QoS & Observability

TimescaleDB + Prometheus + Grafana for MOS score monitoring, bitrate analytics, packet-loss alerts, and autoscaling triggers.

Deployment Modes

Architecture at a Glance

Your users’ browsers connect via DTLS-SRTP to a horizontally scaled media server SFU cluster. A Redis Streams backbone handles room state across nodes. AI pipelines (Deepgram, Whisper, LLM) run as sidecars consuming audio from the SFU. FFmpeg workers transcode for HLS broadcast. All components run in Docker containers — deployable on AWS, DigitalOcean, Azure, or bare-metal on-premise. A Prometheus + Grafana stack gives full visibility into session quality and cluster health.

Who This Is For

  • BFSI: vKYC & Financial Advisor Calls
  • Healthcare: Telemedicine Platforms
  • EdTech: Virtual Classrooms
  • Automotive: Remote Diagnostics
  • Events: Virtual Conferences
  • Media: Live Sports & News Streaming
  • Enterprise: All-Hands & Town Halls
  • OEM: Embedded Video Features

CentEdge vs The Alternative

Off-the-shelf CPaaS (Twilio, Daily, LiveKit)
  • Pay-per-minute pricing escalates with scale
  • Data routed through vendor's global infrastructure
  • No control over codec, routing, or AI features
  • White-labelling limited or unavailable
  • Compliance certifications require vendor approval
CentEdge Custom Build
  • Fixed project cost — no per-minute exposure
  • Deploy on your own servers or private cloud
  • Full control over media pipeline, AI, and features
  • 100% white-labelled under your brand
  • GDPR, HIPAA, PCI-DSS built to your requirements

Technology Stack

Media Server SFU

Node.js

React / React Native

C++ LibWebRTC

FFmpeg

Redis Streams

gRPC

Deepgram

OpenAI Whisper
Prometheus + Grafana
TimescaleDB
Docker / K8s

Frequently Asked Questions

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How is this different from just licensing Zoom or Teams?

Zoom and Teams are SaaS products hosted on Microsoft or Zoom's infrastructure — your call data, recordings, and transcripts are on their servers. A CentEdge build gives you a completely custom platform hosted on your own infrastructure, with no per-user licensing, no vendor lock-in, full white-labelling, and the ability to add any AI feature you need. For BFSI and Healthcare clients where data residency is mandatory, there is no viable SaaS alternative.

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What scale can the platform handle?

The horizontally scaled media server architecture CentEdge builds is designed to handle 10,000+ concurrent sessions per cluster, with additional nodes added automatically via the autoscaler as load increases. For enterprise deployments requiring 100,000+ concurrent users, a multi-region cluster topology is used with load-balancing at the signalling layer.

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Which browsers and devices are supported?

The platform supports all modern browsers — Chrome, Firefox, Safari (desktop and iOS), and Edge — without plugins. Native mobile SDKs are available for iOS and Android via React Native. For embedded devices (IoT, kiosks, industrial displays), a C++ LibWebRTC SDK is available.

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How is recording handled — where is the video stored?

Recording is handled via a headless Chromium container that joins the call as a participant and captures the mixed stream. The output is saved as MP4, then optionally converted to HLS for streaming playback. Storage can be on AWS S3, DigitalOcean Spaces, Azure Blob Storage, or an on-premise NAS — fully configurable per your data residency requirements.

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Can we add AI transcription and meeting notes to the conferencing platform?

Yes. Real-time transcription via Deepgram or Whisper can be embedded directly into the conferencing platform, with LLM-generated summaries and action items surfaced in the UI after each call. This is available as part of the video conferencing build or as a separate transcription layer added to an existing platform.

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How long does a custom build take?

A production-ready MVP with core conferencing, recording, and basic AI features typically takes 10–14 weeks. Adding live streaming, advanced AI analytics, or multi-region deployment extends this to 16–20 weeks. CentEdge uses its own production-tested infrastructure components — media server, signalling, autoscaler, monitoring — as a starting point, significantly reducing time-to-production compared to greenfield development.

GET IN TOUCH

Let’s Build This
Together

Tell us about your project and we’ll return with an architecture overview and engagement proposal within 48 hours.

  • hello@centedge.io
  • +91 6362 814071
  • T-Hub, Hyderabad, India
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