Soluciones
Scale-up de SaaS B2BPlataforma ML para puntuación de clientes
Camino de producción desde notebooks hasta servicios monitorizados — features, registro y despliegue seguro para modelos orientados a ingresos.
Data science had strong notebooks but weak production paths. We built feature pipelines, a model registry, and deployment patterns so scoring services could ship with the same bar as any customer-facing API.
Cómo lo abordamos
Feature paths
Batch and online feature patterns with shared entity keys, freshness checks, and reuse across models.
Registry & release
Versioned artifacts, canary deploys, and automated evaluation gates before traffic shifts.
Governance hooks
Approvals, audit trails, and responsible-AI checks appropriate to customer and revenue use cases.
Lo que entregamos
- Patrones de feature store y serving batch + online
- Registro de modelos, despliegue y lanzamientos canary
- Monitorización de deriva, evaluación y paneles
- Puntos de gobernanza para aprobaciones y auditoría
Resultados
Monitored models with drift and business KPIs in one place
Repeatable release train instead of one-off handoffs
Room to add adjacent models without new bespoke plumbing
Stack representativo