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Drag, drop, deploy — CI/CD discipline for every training workflow.

Pipeline Forge

Provides a drag-and-drop DAG builder for constructing multi-step ML training pipelines with built-in retry logic, dependency management, and parallel execution. Brings CI/CD discipline to model training workflows in organizations where training steps are currently managed as fragile shell scripts.

Why It Matters

PipelineForge replaces the fragile shell scripts holding most enterprise ML training together with visual, disciplined, repeatable pipelines.
A drag-and-drop DAG builder brings the reliability standards of software CI/CD — retries, dependency management, parallel execution — to workflows that currently break silently at 2 AM.
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Kills the shell-script fragility

Training workflows managed as ad-hoc scripts fail without warning and depend on one person's tribal knowledge — visual DAGs with built-in retry logic make pipelines self-documenting and self-healing.

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CI/CD discipline for ML

Dependency management and automated execution bring the same rigor to model training that engineering teams already trust for software releases.

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Run anywhere, no lock-in

Support for both cloud-native (Vertex Pipelines, SageMaker Pipelines) and self-hosted execution lets enterprises standardize one pipeline practice across hybrid environments.

The Cloudly Advantage

PipelineForge is the connective tissue of the Cloudly platform — the orchestration layer that wires DataQualityGuard, TrainForge, ExperimentHub, and FeatureVault into automated end-to-end workflows.
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CI/CD Implementation flagship

Every PipelineForge deployment is a CI/CD consultancy engagement by definition — the tightest product-to-service revenue linkage in our portfolio.

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Platform glue that raises deal size

Orchestrating our other products into one automated workflow turns single-product deals into platform contracts.

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Visual builder widens the audience

Drag-and-drop accessibility lets data scientists and analysts build pipelines without DevOps help — reinforcing the democratization story started by AutoML Accelerator.

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Airflow and Kubeflow services pull-through

Deploying and operating Kubeflow, Airflow, and Prefect stacks is core DevOps consultancy and Cluster Services work with ongoing managed-operations revenue.

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Step Functions opens AWS deals

Native AWS Step Functions support creates entry points for AWS Migration and Monitoring services in cloud-committed accounts.

The Final Takeaway

Hybrid execution wins regulated deals — Self-hosted pipeline execution satisfies data-residency mandates in BFSI and healthcare — deals hyperscaler-only orchestrators can't close.

Powered By

Kubeflow Pipelines

Core to the PipelineForge technology stack.

Apache Airflow

Core to the PipelineForge technology stack.

Prefect

Core to the PipelineForge technology stack.

AWS Step Functions

Core to the PipelineForge technology stack.

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