Getting Started with Leora:

Leora delivers customized recommendations using our proprietary Leora base recommendation model, fine-tuned on client data to drive personalized suggestions across e-commerce, music, video, and social feeds.

Main features:

Each customer benefits from:

• Custom fine‑tuning: Our Leora base model is optimized on your data for maximum relevance.

• Flexible data support: Ingest heterogeneous inputs—user profiles, event logs, content metadata—via schema-driven pipelines.

• Low‑latency inference: Retrieve real‑time recommendations through a secure, scalable HTTP API served from heyleora.com.

Use cases include next‑item suggestions in digital storefronts, dynamic playlist generation, personalized video queues, and tailored social content streams.

Architecture Overview:

• Ingestion Service: Validates payloads, enforces schema, and stages data into isolated S3 buckets.

• Schema Registry: Stores JSON schema definitions; defines required fields, data types, cardinalities.

• Training Orchestrator: Schedules fine‑tuning jobs on GPU clusters (Kubernetes + CUDA + Triton). Supports early‑stop and dynamic resource scaling.

• Model Registry: Versioned storage (S3/Git‑LFS) mapping client_id + datastore_id to trained checkpoints.

• Inference Service: Triton‑backed gRPC/REST endpoint providing top‑K item scores with optional explanations.

• Monitoring & Logging: Prometheus metrics (latency, throughput, GPU utilization), ELK stack for log aggregation.

• API Gateway: Centralized entry‑point handling authentication, rate‑limit (default: 100 req/s per API key), and routing.