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From legacy core systems to ML-ready features — without months of data engineering.

ETL Forge

Generates and operates production-grade data ingestion and transformation pipelines from source systems (banking core systems, telecom OSS/BSS, industrial historians) to ML feature stores and training datasets. Removes the months-long data engineering work that delays ML project delivery in enterprises with complex legacy source systems.

Why It Matters

ETLForge tackles the unglamorous work that actually delays enterprise ML — getting data out of legacy core systems and into ML-usable form.
Pre-built connectors for T24, FLEXCUBE, and telecom mediation platforms compress the months of custom data engineering that stall projects before a single model gets trained.
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The real ML bottleneck is extraction

In traditional enterprises, models wait months not for data science but for pipelines from core banking and OSS/BSS systems — automated pipeline generation removes the longest pole in every project plan.

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Legacy connectors nobody else builds

T24 Temenos, Oracle FLEXCUBE, and telecom mediation connectivity is specialist knowledge modern data tools skip — precisely the systems our target enterprises run their businesses on.

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Production-grade, not throwaway scripts

Generated pipelines ship with orchestration, monitoring, and operations built in — infrastructure that survives handoffs, not one-off extracts that break silently.

The Cloudly Advantage

ETLForge is the on-ramp that connects our clients’ legacy reality to everything else Cloudly sells — the pipelines that fill DataLakeML, feed FeatureVault, and supply TrainForge.
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Legacy connector moat

T24 and FLEXCUBE connectivity is deep vertical IP tuned to the systems running banking in our markets — a differentiator that compounds with every mediation platform and historian we add.

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Unblocks every platform sale

"Great platform, but our data is stuck in core banking" is the objection ETLForge deletes — the enabler that converts platform interest into platform contracts.

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Data engineering services engine

Airflow, Glue, dbt, and Spark pipeline builds are sustained consultancy engagements with managed-operations tails — heavyweight, long-duration revenue like DataLakeML.

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Natural DataLakeML bundle

The lake plus the pipelines that fill it is one architecture conversation — bundled, they're a complete data foundation deal at twice the scope.

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Fivetran and Glue pull-through

Managed connector platforms and AWS Glue ETL open AWS Migration conversations while modern-stack expertise keeps us credible beyond legacy.

The Final Takeaway

Fastest time-to-first-model pitch — Cutting months off data preparation is often the difference between an AI initiative shipping this fiscal year or dying in planning — urgency BD can sell to executives with deadlines.

Powered By

Apache Airflow

Core to the ETLForge technology stack.

AWS Glue ETL

Core to the ETLForge technology stack.

GCP Dataflow

Core to the ETLForge technology stack.

Fivetran

Core to the ETLForge technology stack.

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