Quickstart
From first conversation to predictions in production.
Onboarding journey
Scope the engagement
Contact your Avra representative at sales@avra.ai. We start by understanding the decisions you want to improve, the data you have, and the integration shape — API, batch, or embeddings — that fits your operation.
Provision your workspace
Avra provisions a tenant-isolated workspace. You receive credentials for app.avra.ai and access to your Data Contract — the agreed schema for the relational data you will send.
Send your data
Stream or upload your relational data through API, connectors, or SFTP. Every event is validated against your data contract; deviations trigger a notification, not a silent failure.
Train your Relational Foundation Model
Avra pre-trains your RFM on your relational schema and temporal business data. For managed deployments, this runs in your tenant-isolated environment. For on-premise deployments, this runs inside your perimeter.
Train downstream models
Task-specific models — credit, fraud, growth, custom — are trained on top of your RFM and the Graph Foundation Model. Each training run feeds signal back into your RFM, making the next iteration sharper.
Promote to production
Validate offline against your holdouts. Mirror against production traffic. Promote when you meet your performance bar. Roll back with one alias reassignment if anything regresses.
Once you are live
Dashboard
Monitor usage, manage models and versions, and govern access
API Reference
Real-time predictions, model discovery, and version control
Batch Inference
Score entire portfolios on a schedule
Embeddings
Use Avra representations as features in your own ML models
Where to go from here
I want to understand the platform first
Read Why Avra, then the Platform Architecture — the three layers, the flywheel, and how they compose.
I want to see specific use cases
Credit Intelligence, Fraud Detection, Growth & Sales, or build your own model with embeddings.
I'm ready to integrate
Start with the API Reference for authentication, endpoints, and integration patterns.