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StrataHub

Capability

Data pipelines that build themselves

AI-assisted data pipelines, automated quality checks, lineage, and modern data stack orchestration

AI-assisted data pipelines, automated quality checks, lineage tracking, and modern data stack orchestration — less hand-coded glue, more shipped data.

We use AI to speed up the data work itself: schema mapping, transformation drafting, and test generation, all reviewed by senior engineers before anything reaches production.

AI-Assisted Pipeline Build

Agent-drafted SQL, data models, and schema mappings reviewed by engineers — cutting the boilerplate without loosening the review standard.

Automated Quality & Lineage

Anomaly detection on freshness, volume, and distribution, wired to lineage graphs so a failure is traceable back to the source that caused it.

Modern Stack Orchestration

Scheduling, dependency management, and environment promotion across your modern data stack, with cost and runtime tracked per job.

Our approach

From audit to ROI in 3 phases

Phase 1

Discover & Audit

Source inventory, lineage gaps, and transformation hotspots, turned into a prioritised pipeline backlog with measurable SLAs.

Phase 2

Build & Integrate

AI-assisted SQL and model drafting, automated quality checks, and lineage instrumentation — reviewed by senior engineers and shipped in 90 days.

Phase 3

Ship & Measure

Anomaly alerts, cost controls, and continuous refactoring to keep warehouse spend and pipeline latency trending down quarter on quarter.

Deliverables

AI-assisted pipeline developmentAutomated data quality checksLineage & cataloguingModern data stack orchestrationWarehouse cost optimisation

ROI snapshot

Pipelines that ship faster and break less — measured in hours saved per engineer per week

↓ 50-70%

Pipeline build time

↓ 60%

Data incidents

flat or ↓

Warehouse cost trend