Architecture
It routes AI tasks through Aiva — the intelligent operations layer — which selects the right model, applies policies, handles fallback, and returns structured output. Built for operators running multiple AI products, not for one-off prompting.
Core architecture
Natural language understanding, intelligent routing, and execution. Aiva interprets your intent, selects the right capability, and returns structured outputs.
Adaptive model selection across providers with fallback logic, capability matching, and policy-controlled cost management.
Cross-session retrieval and context persistence for apps that need intelligent continuity across requests.
App-scoped agents with dedicated behavior constraints, capability policies, and per-app model selection.
Provider keys, capability restrictions, adult content controls, and execution policies built into the orchestration core.
Website, API, and admin console all map to one underlying operating model — one place to build, test, and deploy.
Execution flow
Describe your task
Tell Aiva what you need in natural language.
Aiva classifies
Routes to the best capability and model for the task.
Policy check
Capability permissions, content flags, fallback rules evaluated.
Execution
Model called with memory hooks and runtime observability.
Output + artifact
Response stored as artifact with provider/model metadata.
Operator trace
Events, usage, and artifacts visible in the operator console.
Smart routing first
Aiva routes to the best model for each task. You are not locked to one provider. Policy, fallback, and cost logic are built in — not bolted on.
Operator control
Not a prompt playground. The operator console manages apps, agents, artifacts, GitHub repos, deployments, and provider configuration from one interface.
Request access for teams that need orchestration quality, reliability, and real operational visibility.