The real-time infrastructure platform for products that outgrow hosted RTC.
Voice. Video. AI. One platform. Self-hostable or managed — signaling, control plane, TURN, SFU, and room-native AI workers in a single TypeScript monorepo.
Provenance & founder
30 years building software. 10+ years of WebRTC. Production at scale.
TomatoRTC is independent new work by Nathaniel Currier after Temasys — WebRTC solutions architect → CTO. Healthcare, government, enterprise.
WebRTC solutions architect → CTO — SDK design, signaling, media, TURN/STUN, platform ops, enterprise integrations.
Not copied from Temasys proprietary source, private repositories, or confidential implementation materials.
Deployment patterns, tenant isolation instincts, observability expectations, voice-AI room model — not prior code or customer IP.
TypeScript monorepo with 600+ tests — protocol, server, clients, TURN, SFU, media-plane, workers, and runnable demos.
Note
PROVENANCE.md (repository root). Similarity to prior systems reflects Nathaniel Currier's general professional knowledge, public WebRTC standards, browser APIs, open-source ecosystem behavior, and newly authored implementation work.Market timing
Three converging markets — RTC, CPaaS, and voice AI.
Every B2B product eventually adds live video, voice, or AI-in-the-room. Hosted SDKs win the first sprint; at scale, buyers hit cost, compliance, and customization walls.
→ $67B by 2032 at ~39.8% CAGR
Mordor Intelligence
2025–2033 at ~39% CAGR — fastest wedge inside conversational AI
Grand View Research
Note
Problem
Hosted RTC optimizes for speed-to-demo, not speed-to-own.
Once teams need tenant isolation, audit exports, room-native voice AI, or predictable unit economics, hosted platforms become a strategic liability.
- Economics Per-minute and per-participant SaaS fees compound as usage grows — voice AI multiplies audio minutes.
- Compliance Regulated buyers need auditable signaling, tenant isolation, and data residency control.
- Voice AI gap Sideband agent APIs route audio outside the product's media boundary; room-native workers are rare.
- Observability Black-box vendors make root-cause analysis a support ticket, not an engineering workflow.
Solution
One platform: protocol, control plane, media, TURN, voice workers.
TomatoRTC ships as a cohesive monorepo — not a signaling SDK plus a separate SFU fork plus a TURN vendor plus a bolt-on agent framework. Integrate once, deploy on your cloud or ours.
Multi-tenant rooms, JWT/OIDC, admin API, hash-chained audit, regional routing.
Mesh + SFU (mediasoup production path), cascaded SFU, simulcast/SVC, integrated first-party engine.
First-party TURN/STUN with dynamic credentials and bandwidth metering.
Service participants — Node/Python/Go/C# SDKs; STT/LLM/TTS via WorkerAdapter; supervisor API.
Voice AI wedge
Room-native agents — the differentiation layer for the next decade of RTC.
Voice-AI spend is growing ~4× faster than core WebRTC. TomatoRTC treats workers as first-class participants: subscribe to remote audio on the SFU path, emit typed outputs, optionally publish synthesized voice back.
- Human participants publish live audio into the room over mesh or SFU paths.
- A service worker joins the same room via WorkerRoomClient with role service.
- The worker subscribes to remote audio, runs VAD turn detection, then STT, LLM, and TTS adapters.
- Structured WorkerOutput events and optional synthesized audio publish back into the room.
Note
Voice AI wedge · market
Fastest-growing segment inside conversational AI.
Broad conversational voice segment
ResearchIntelo
Whisper, Deepgram, OpenAI, Anthropic — swap adapters without forking the room runtime
Workers subscribe on the SFU path — raw media stays on customer boundary, not a sideband API
Per-room worker spawn, typed WorkerOutput, optional TTS publish-back into room mix
Product
Deep enough to differentiate. Honest about what is production today.
Production SFU media runs on mediasoup. Signaling, auth, TURN, tenant policies, reconnect, chat, data channels, diagnostics, AI worker foundations, and client-ai perception are implemented with tests and runnable examples.
Mesh/SFU, chat, DC, diagnostics, client-ai VAD on supported browsers
WebSocket + alt transports; tenant isolation; admin API
WorkerRoomClient, supervisor API, transcription/assistant adapters
mediasoup production SFU; first-party integrated engine in hardening
Note
Product · status matrix
Layer-by-layer production reality.
Note
Why we win
Control-plane depth + room-native voice AI + first-party TURN.
LiveKit proved demand for self-host SFU and agents. TomatoRTC targets buyers who also need tenant-scoped auth, audit exports, and relay economics — and AI workers on the same protocol as humans.
Business model
Two revenue lines — license the platform or run it for them.
Hosted RTC solves distribution. It does not solve ownership. Deep enough to differentiate. Simple enough to deploy.
Self-managed licensing
- ✓ Annual/term platform license (source + releases + support tier)
- ✓ Expansion via seats, regions, worker workloads, support SLAs
- ✓ Customer bears infra — we capture software margin
- ✓ Land with dev teams; expand as production traffic grows
Managed solution
- ✓ Fixed monthly solution cost = pass-through infra + management fee
- ✓ TomatoRTC operates signaling, SFU, TURN, AI worker supervisor
- ✓ Higher ACV, longer contracts, services attach
- ✓ Land with teams that want ownership without ops headcount
Business model · TCO
Flat license vs compounding hosted per-minute fees.
Cost divergence increases over time. Hosted RTC: ↗ rapidly increasing. TomatoRTC: ↗ shallow, predictable growth.
Traction & maturity
Platform built — commercial motion next.
Core signaling, browser media, workers, metering, operator tooling, and bounded PMG slices ship with code and evidence. The next phase combines repeatable sales and design partners with focused production hardening.
protocol, server, client-browser, client-ai, TURN, SFU, media-plane, workers, examples
mediasoup production path plus integrated first-party engine under hardening
Supervisor API, transcription/assistant adapters, kitchen-sink AI perception demo
B2B SaaS, teams exiting Twilio/Vonage managed APIs, regulated verticals — LOIs in validation pipeline
Moat & roadmap
Own the protocol layer and you own the platform economics.
Owning signaling + tenant policy + TURN + optional first-party media creates switching costs and margin that a thin SDK wrapper cannot match.
UDP RTP/RTCP, pacing, DTLS/SRTP termination — reduces mediasoup dependency for control-sensitive buyers.
Auth, audit hash chain, admin API, regional policy — hard to replicate by bolting onto a generic SFU.
WorkerOutput on room chat + optional audio publish — same integration surface for humans and AI agents.
Note
Moat · roadmap priorities
What compounds the platform advantage next.
Developer Adoption → Ecosystem → Integrations → Data → Platform Advantage.
Support bundles, OTLP, topology — lowers cost-to-serve and increases trust in enterprise deals.
First-party congestion control, live recording/WHEP proof, native media parity, and broader browser-matrix CI.
Multi-region reference deploys, runbooks, and failover drills for teams that want ownership without headcount.
Note
Go-to-market
Developer-led land, platform expand, managed upsell.
ICP: B2B SaaS with backend teams, teams outgrowing Twilio Video's narrowed vertical focus or Vonage's Ericsson-owned managed model, regulated verticals, and voice-AI builders who need room-native agents. Motion: kitchen-sink eval → pilot → license or managed contract.
Open-source examples, docs, demo menu, AI worker supervisor, competitive executive summary.
More regions, voice worker workloads, enterprise auth/audit, support tier upgrades.
Self-managed license → managed solution when customer wants us to operate the plane.
SI/consultancies for Twilio Video and Vonage managed API exits; vertical specialists in health/fintech/edtech.
Go-to-market · market
TomatoRTC sits at the intersection of three growing markets.
Core infrastructure market at 39.8% CAGR
Mordor Intelligence
Fastest wedge inside conversational AI at 39% CAGR
Grand View Research
Communications platform market — migration opportunity
Metrigy
Building the commercial layer on a shipped platform.
The technical foundation is largely built — this round accelerates revenue and production hardening where it unlocks ACV.
- 1 Design-partner deployments
Onboard 3–5 design partners across B2B SaaS, teams exiting managed API lock-in (Twilio vertical narrowing, Vonage/Ericsson risk), and regulated verticals.
- 2 Managed ops + native media
Multi-region reference deploys, runbooks, and proven Swift/Kotlin media packaging and interop.
- 3 Voice-AI reference architectures + GTM
Reference integrations, competitive enablement, and go-to-market for migration and AI-native segments.