Layer 01 · Entry Channel
The entry point. The channels where users connect with intelligent systems — from messaging to voice.
Type
Omnichannel entry point
Target latency
< 200 ms per response
Protocol
HTTP · WebSocket · PSTN
Output
Structured intent to Layer 2
Layer 02 · Orchestration
The conversational brain. Agents that understand context, reason about intent, and orchestrate actions across the system.
Core technology
LLM + Tool Use + Memory
Memory
Session context · Long-term RAG
Capabilities
Understands · Reasons · Acts
Output
Structured action to Layer 3
Layer 03 · Business Domain
Specialized modules that automate complex business processes with domain logic orchestrated by AI.
Pattern
Domain-specific applications
Integration
Internal APIs + AI Models
Output
Business decisions and actions
Layer 04 · Active Intelligence
The active intelligence layer. Models that process language, vision, signals, and patterns — in real time.
Base models
Proprietary + Open Source
Inference
Real-time · Batch
Latency
50–500 ms depending on model
Integration
REST / gRPC APIs
Layer 05 · Prediction
Real-time scoring and prediction. Trained models that generate actionable values for every transaction or customer.
Model type
XGBoost · LightGBM · Neural networks
Update
Continuous via Layer 6
p99 latency
< 30 ms per score
Layer 06 · MLOps
The pipeline that keeps models up to date. A continuous cycle from raw data to models monitored in production.
Platform
MLflow · Vertex AI · SageMaker
Frequency
Continuous · Scheduled · On-demand
Drift detection
Data drift · Concept drift
Delivery
Versioned models to Layer 5
Layer 07 · Foundation
The foundation. The quality of all artificial intelligence depends on the quality, completeness, and governance of the underlying data.
Storage
Data Lake · Data Warehouse · Vector DB
Processing
Streaming · Batch · Real-time
Quality
Validation · Lineage · Cataloging
Layer 08 · Platform
The platform that makes everything else possible — reliably, securely, and at scale. The ground everything runs on.
Cloud
GCP · AWS · Azure · On-prem
Compliance
SOC 2 · GDPR · LFPDPPP
Target SLA
99.9% uptime
Observability
Logs · Traces · Metrics
AI generating business value
Higher conversion
More approved customers at the same or lower risk.
Smarter approval
Decisions in seconds with full customer context.
Less fraud
Real-time detection before the damage happens.
Better experience
24/7 support that actually resolves issues — no escalation to humans.
Efficient operations
Automation that scales without scaling the team.
DashOne embeds engineers with your team to take this architecture to production — in weeks, not years.