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AI & Real-Time Automation

AI Voice, Vision & Real-Time Intelligence

From AI-powered call centers and voice-controlled ERP to real-time LLM streaming and computer vision pipelines - OpenCollar builds automation that sees, hears, speaks, and acts in milliseconds, not minutes.

AI Voice, Vision &

What You Get

AI Call Center & Voice Agents

Deploy AI agents that handle inbound and outbound calls with natural conversation, real-time sentiment detection, and seamless human handoff. Built on Twilio, WebRTC, and SIP with sub-200ms response latency.

Voice-Controlled ERP & CRM

Give your team hands-free access to business data. 'Show me last month's revenue for the East region' - AI processes the voice command, queries your ERP/CRM, and speaks or displays the answer in real-time.

Real-Time LLM Streaming

Stream LLM responses token-by-token via WebSockets and Server-Sent Events for instant conversational AI interfaces. Supports GPT-4, Claude, Llama, and Mistral with <100ms first-token latency.

Computer Vision Automation

Real-time video analysis for quality inspection, safety monitoring, inventory counting, and document processing. Edge-deployed models process 30+ FPS with instant alerting on anomaly detection.

Generative AI Integration

LLM-powered features including AI copilots, content generation, code assistance, and conversational interfaces. We fine-tune and deploy GPT, Claude, Llama, and open-source models for your specific domain.

MLOps & Real-Time Model Serving

End-to-end ML lifecycle management with real-time inference APIs that handle 10K+ requests/second. Model versioning, A/B testing, automated retraining, drift detection, and explainability dashboards.

Our Process

1

Use Case Discovery

We identify your highest-impact real-time AI opportunities - whether voice, vision, or streaming LLM - and build a prioritized roadmap with projected ROI and latency requirements.

2

Data & Infrastructure Setup

Configure real-time data pipelines (Kafka, WebSocket, SIP/WebRTC), prepare training datasets, and provision GPU inference infrastructure for sub-second response times.

3

Model Development & Integration

Build, fine-tune, and integrate AI models into your existing systems. Voice models trained on your domain vocabulary, vision models calibrated to your environment, LLMs grounded in your data.

4

Deploy, Monitor & Optimize

Production deployment with real-time monitoring dashboards, automated scaling, latency tracking, and continuous model improvement based on live performance data.

Key Deliverables

AI voice agent with Twilio/WebRTC/SIP integration
Real-time LLM streaming API (WebSocket + SSE)
Computer vision pipeline with edge deployment
Voice-to-action ERP/CRM integration
Real-time inference APIs (< 200ms latency)
MLOps infrastructure with drift detection & auto-retraining
Performance monitoring & latency tracking dashboard

Why Choose Us

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200+ AI/ML models deployed in production across healthcare, finance, and logistics
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Real-time systems handling 10K+ concurrent voice sessions and 30+ FPS video analysis
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Deep expertise in Twilio, WebRTC, SIP, Kafka, and edge computing for sub-second latency
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Full-stack AI team: ML engineers, voice UX designers, MLOps specialists, and infrastructure architects
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From proof-of-concept to production in as few as 6 weeks

Build AI That Sees, Hears & Acts in Real-Time

Book a free AI readiness assessment. Our engineers will evaluate your real-time automation opportunities and map a clear path from prototype to production.