Canonical AI system architecture.
Eight layers from signal to governance. One stack, many configurations.
Eight layers of intelligence
Every system we build follows this architecture. Hover to explore each layer.
Signal Intake
Data Intelligence
Retrieval & Memory
Model Reasoning
Orchestration
Action Layer
Monitoring & Safety
Governance
One stack, four configurations
Each variant emphasizes different layers. Select a variant to see which layers light up.
Voice-first
Real-time conversational AI with sub-second latency.
Vision-first
Frame-level detection, tracking, and classification pipelines.
RAG-heavy
Deep retrieval with citation grounding and multi-source memory.
Agentic
Autonomous multi-step execution with policy-bounded tool use.
System pattern overlays
Repeatable blueprints that map onto the canonical stack.
RAG system blueprint
Retrieval-augmented generation with citation grounding and multi-source memory.
Social message connectivity
Multi-channel intelligence layer for WhatsApp, Slack, Teams, and more.
Vision detection pipeline
From raw frames to structured actions via detection and tracking.
Boundaries and control
Intelligence without guardrails is risk. These constraints are built into every layer.
Map this architecture to your environment.
Tell the AI about your stack and signals. It will configure the layers.