Conversational AI Blueprint
Signal → NLP → Intent → Route → Execute → Respond → Learn. From raw messages to qualified leads and automated workflows.
Seven-Stage Processing Pipeline
Every inbound message flows through this pipeline — from raw signal to intelligent action and continuous learning.
Signal Intake
Capture user messages from any channel in real time.
Inbound signals arrive from web chat, WhatsApp, Slack, Teams, SMS, email, or voice (STT). Each message is normalized into a common envelope — text, sender context, channel metadata, conversation history — and pushed onto the processing queue with sub-100ms latency.
Signal → Intent → Workflow
Watch a real message flow through the pipeline — from raw input to classified intent to automated action.
"I'd like a demo of your AI voice system for our call center."
Intent → Workflow Mapping
Each classified intent triggers a specific automated workflow. Click any intent to see its full action chain.
Lead Generation Pipeline
Intent: request_demo
Smart Confidence Thresholds
Not every intent is classified with equal confidence. The system routes by certainty — auto-execute, clarify, or escalate.
Auto-Execute
> 85%High-confidence intents proceed directly to workflow execution. No human needed.
Clarify
60 – 85%Ambiguous signals trigger a clarification question before routing to a workflow.
Escalate
< 60%Low-confidence or sensitive signals are escalated to a human agent immediately.
Automate conversations into workflows.
Describe your channels, intents, and business processes. We'll architect the NLP pipeline, workflow routing, and integration layer.