Rigorous provides an integrated MLOps platform that lets data and ML engineering teams define, schedule, and run DAG‑based pipelines via declarative YAML or a visual editor on Kubernetes, Spark, or serverless back‑ends. The system automatically captures code, data lineage, and artifact versions, and offers real‑time monitoring dashboards, alerts, and role‑based access controls for reproducible, auditable production workflows.
Funding
Funding not disclosed
Founders
Product
Problem
Data science and machine learning teams often rely on a patchwork of tools for pipeline orchestration, monitoring, and version control, which creates operational friction, reduces reproducibility, and hampers scaling of production workloads.
Solution
Rigorous delivers a single platform that consolidates pipeline definition, execution, observability, and artifact management for complex data and ML workflows. Users compose directed acyclic graphs (DAGs) through a declarative YAML schema or visual editor, then run them on shared compute back‑ends such as Kubernetes, Spark, or serverless runtimes. The system automatically records metadata, code versions, and data lineage, enabling reproducible experiments and audit trails. Real‑time dashboards surface execution metrics, logs, and alerts, while built‑in CI/CD hooks allow seamless promotion of pipelines from development to production. APIs and SDKs provide programmatic access for integration with existing tooling, and role‑based access controls enforce security and compliance across teams.
Target Audience
The primary customers are data engineering and machine learning engineering teams in mid‑size to large enterprises that need a reliable, scalable MLOps infrastructure for productionizing data pipelines and ML models.
Features
- Declarative pipeline authoring via YAML and drag‑and‑drop visual editor for DAG construction
- Native scheduler and distributed executor supporting Kubernetes, Spark, and serverless runtimes
- Automatic lineage tracking and versioned artifact storage linked to Git repositories
- Real‑time monitoring dashboard with metric visualizations, log aggregation, and configurable alerts
- RESTful API and Python SDK for programmatic pipeline control and integration with CI/CD pipelines
- Role‑based access control (RBAC) and immutable audit logs for security and compliance
- Extensible plugin framework allowing custom operators and connectors to external data sources