Conversational AI and real-time streaming app development services

The infrastructure decision you make in week one, Agora, Twilio, or in-house WebRTC, determines whether your platform scales affordably or becomes a cost problem at 50,000 users. We've made this choice across dozens of real-time and AI voice builds. We help you get it right from the start, then ship in 8 to 12 weeks.

  • Scale to millions of concurrent users with cloud-native architecture, cost-modelled for your actual usage before work starts

  • Ultra-low latency for real-time messaging and video streaming, WebRTC under 200ms or low-latency HLS for broadcast scale

  • Production-grade uptime for mission-critical communication platforms, not a prototype you'll need to rebuild at scale

In short

RaftLabs builds conversational AI voice agents, live streaming platforms, and real-time messaging systems for companies that need production-grade infrastructure without paying per-minute managed service costs at scale. We help you choose between Agora, Twilio, and in-house WebRTC based on your actual user count and cost model, then ship in 8 to 12 weeks at a fixed price. No vendor lock-in, full source code ownership.

Recognition

Sound familiar?

  • Paying per-minute for a managed streaming or voice service that was affordable at 1,000 users but becomes the biggest line on your cloud bill at 100,000?

  • Voice agents trained on generic models that stall when a customer asks anything specific, and your team manually handles the escalations that should have been automated?

01 Diagnosis

Problems we solve in conversational AI and real-time streaming

  1. 01
    Problem

    Your support team handles the same 50 questions repeatedly and the chatbot you deployed doesn't fix it

    Solution

    Most chatbot deployments fail the same way: they handle the 20 scripted scenarios that were in the spec and escalate everything else. The support queue doesn't shrink because the bot doesn't resolve, it just deflects. According to ContactBabel's 2024 industry analysis, the average cost per inbound call handled by a human agent is $5.50, versus $0.50–$1.30 for a voice AI interaction, an 80–92% cost reduction per automated call. That gap only materialises when the AI actually resolves the query. Conversation systems trained on your actual support history, with intent detection tuned to your product vocabulary and escalation logic that triggers on genuine complexity rather than on any question outside the script, resolve the queries that cost your team the most time.

  2. 02
    Problem

    Your product needs real-time audio or video between users but you're not sure whether to build on Agora, Twilio, or WebRTC directly, and the wrong choice will cost you later

    Solution

    The infrastructure decision between Agora, Twilio, and self-hosted WebRTC is a cost-model decision as much as a technical one. Agora and Twilio are the right choice at lower concurrency and faster time-to-market. Per-minute pricing works when your user count is manageable. At high scale, the same pricing model becomes the largest line on your cloud bill. Self-hosted WebRTC eliminates per-minute costs but requires significant infrastructure investment. We model this decision based on your target concurrency and cost model before committing to an architecture.

  3. 03
    Problem

    Your live events have a 5 to 15 second delay that makes audience interaction: Q&A, polls, reactions, feel disconnected from what's happening on screen

    Solution

    HLS streaming at broadcast scale introduces a 5 to 15 second latency gap. That's acceptable for passive viewing but it breaks interactive formats. When the audience's reaction to a live poll arrives 10 seconds after the presenter moves on, the interactive layer feels disconnected. WebRTC-based interactive streaming at sub-200ms latency is the right architecture for event formats where audience participation is the product. The trade-off is a lower concurrent viewer ceiling, which is why many platforms use both: HLS for the main broadcast and WebRTC for the interactive overlay.

  4. 04
    Problem

    Your AI voice agent prototype handles scripted scenarios well but breaks on real customer conversations

    Solution

    Voice agent prototypes built on generic conversation models handle the demo scenarios and fail on production conversations. Real customer calls include ambiguous phrasing, product-specific terminology, multi-part requests, and frustration signals that generic models don't handle. Voice agents trained on your actual call transcripts, fine-tuned for your product vocabulary, and tested against your real edge cases behave differently in production than in the demo. The difference between a prototype and a production voice agent is the edge case coverage.

02 What we ship

Conversational AI and streaming software we ship

  1. Conversational AI voice agents

    Production voice agents built on a real-time streaming stack: Deepgram for speech-to-text, GPT-4o or a fine-tuned model for conversation logic, and ElevenLabs or a custom TTS engine for audio output. End-to-end latency under 800ms for a natural conversation cadence. Intent detection tuned to your product vocabulary and edge cases, not a generic call centre prompt. Escalation logic triggers on genuine complexity and hands off cleanly to a human agent with full conversation context. Used for customer support, appointment booking, triage, and outbound qualification workflows.

  2. Real-time streaming infrastructure

    Infrastructure choice between WebRTC, Agora, Twilio, and self-hosted media servers is made against your actual concurrency targets and cost model before committing to an architecture. WebRTC delivers sub-200ms latency for interactive sessions. HLS handles broadcast-scale delivery for 100K+ concurrent viewers. CDN selection, edge caching, and adaptive bitrate encoding are configured for your audience geography. For platforms where per-minute managed service pricing becomes prohibitive at scale, we design the migration path to self-hosted infrastructure from the start rather than re-architecting after the cost problem appears.

  3. AI chatbot and messaging systems

    Chat systems with intent detection trained on your actual support history, not scripted to the 20 scenarios that were in the spec. Conversation flows handle multi-turn dialogue, ambiguous phrasing, and product-specific terminology. Escalation logic routes genuinely complex queries to human agents with full conversation context attached. Routine queries resolve without human involvement. CRM integration (Salesforce, HubSpot, Zendesk) routes conversation data, triggers workflows, and syncs records automatically. Real-time messaging layer with WebSocket delivery, typing indicators, read receipts, and message history included as standard.

  4. Custom video conferencing platforms

    Multi-party video conferencing platforms built for specific product contexts: telehealth consultations, online tutoring, team collaboration, or customer-facing video support. WebRTC-based architecture with SFU media routing for group sessions. Features include session recording with automatic cloud storage, screen sharing, breakout room management, participant controls, and waiting room logic. Custom UI built to your brand and UX requirements rather than embedded third-party widgets. HIPAA-compliant session handling available for healthcare contexts. Integration to scheduling, CRM, and post-session reporting systems.

  5. Live streaming platforms

    Live streaming platforms designed for two distinct product formats: broadcast delivery (HLS, CDN-distributed, adaptive bitrate, 100K+ concurrent viewers) and interactive streaming (WebRTC-based, sub-200ms latency, audience participation as the product). Many platforms need both: HLS for the main broadcast feed and a WebRTC layer for the interactive overlay (polls, Q&A, reactions, live gifting). CDN selection, origin redundancy, and auto-scaling infrastructure are sized for your expected peak concurrent load. Automatic recording and VOD pipeline so streams publish to on-demand within minutes of ending.

  6. Real-time collaboration tools

    Multiplayer collaboration systems, shared documents, whiteboards, design canvases, code editors, and structured data forms, built on operational transform (OT) or CRDT-based conflict resolution so concurrent edits from multiple users merge cleanly without data loss. The presence layer shows who is active, where their cursor is, and what they're editing. Change attribution and version history let collaborators see who changed what and roll back when needed. WebSocket infrastructure is designed for your concurrent user count and session duration. Used for SaaS products where real-time collaboration is the core product differentiator.

Companies we've built for

Vodafone
Nike
Microsoft
Cisco
T-Mobile
Aldi
Heineken
GE

03 Track record

What conversational AI and streaming teams get when they work with us

Routine inquiries handled by chatbots without human intervention
80%
Higher engagement with live streams vs pre-recorded video
10x
Average live stream viewing session (8x longer than on-demand)
25 min

04 Case studies

Case studies

05 Client voices

What our clients say

Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.

Amer Abu Khajil
Amer Abu Khajil
Canada flagCanada
Co-Founder and CEO, Perceptional

The project was delivered on time, and within the budget we had agreed upon. Really satisfied.

01 / 02

06 Why us

Why choose us?

  1. 01

    Only what you need

    Every feature ties to a specific business goal. You get what you need to launch. Not a bloated spec that takes twice as long and ships half-baked.

  2. 02

    We show up

    Production fire at 11pm? We're there. We take ownership, fix fast, and keep your business running when it matters. No hiding behind tickets.

  3. 03

    Expert, not yes-men

    If the idea won't work, we say so before a line of code is written. Honest advice saves you more than a team that nods along.

07 Questions

FAQs

We develop NLP chatbots, voice assistants, virtual assistants, customer service bots, sales automation bots, and enterprise conversational AI platforms across web, mobile, and voice channels.

Yes. We integrate conversational AI solutions with Salesforce, HubSpot, Zendesk, Microsoft Dynamics, and custom CRMs through APIs and webhooks. The integration architecture routes conversation data, triggers workflows, and syncs records without requiring manual data transfer.

Yes. We build platforms that combine live streaming with automatic recording and on-demand playback. The VOD pipeline is designed alongside the live infrastructure so recordings are publish-ready within minutes of the stream ending, not hours.

Infrastructure choice is the primary lever: WebRTC for sub-200ms interactive sessions, low-latency HLS for broadcast scale. CDN selection, edge caching, and adaptive bitrate configuration are set for your target audience geography. We test against your target concurrency during load testing, not after launch.

Most projects deliver in 8 to 12 weeks. The timeline depends on the infrastructure choice, the complexity of conversation logic or interactivity requirements, and the integration scope. Fixed cost, agreed before work starts.

Related services

  • AI Agent Development, Autonomous voice and text agents for customer support, sales qualification, and real-time media interaction
  • Custom Software Development, Custom conversational AI platforms, real-time streaming infrastructure, and WebRTC applications built for your concurrency and latency requirements
  • Business Process Automation, Automate conversation routing, transcript processing, media event workflows, and post-session reporting

Talk to us about your conversational AI or streaming platform.

Tell us your use case, target concurrency, and infrastructure preference. We'll help you make the right infrastructure choice before committing to an architecture.

  • Scope and cost agreed before work starts. No surprises. No obligation.
  • Working prototype within 3 weeks of kickoff.
  • Pay by milestone. You see progress before each invoice.
  • 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
  • All conversations are NDA-protected.