Data & Technology · Data Engineering
A governed, real-time data foundation your AI strategy can run on.
We modernise fragmented data estates into lakehouse-grade platforms — trusted, observable and cost-efficient — so decisions, reporting and AI all draw from the same source of truth.
Data platformGOVERNED
AppsAPIsFilesStreams
BronzeRaw ingest
SilverModelled & tested
GoldCurated products
Consumers
BI & reportingAI / MLApplications
What we deliver
From ingestion to a trusted lakehouse.
01
Ingestion & integration
Batch and streaming pipelines from apps, APIs, files and third-party sources into one governed platform.
02
Lakehouse & modelling
Medallion architectures, dimensional models and dbt-driven transformations that stay maintainable.
03
Real-time & streaming
Event pipelines and CDC for low-latency data products, operational analytics and live features.
04
Governance & quality
Data contracts, lineage, cataloguing, access controls and automated data-quality testing.
05
Observability & reliability
Freshness, volume and schema monitoring so issues surface before they hit reporting or models.
06
Cost & performance (FinOps)
Right-sized compute, storage tiering and query tuning to keep the platform fast and affordable.
Stack & tools we work in
Databricks
Snowflake
BigQuery
dbt
Apache Spark
Kafka
AirflowDelta LakeUnity Catalog
FivetranGreat Expectations
AWS
Azure
GCPThe AI-native difference
AI woven through the build — not bolted on.
Agents accelerate the build
Pipeline scaffolding, transformation code and test generation are AI-assisted from day one.
Cyborg Team delivery
A lean, senior pod owns the platform end to end — fewer people, more accountability.
Built for AI workloads
Governed, well-modelled data that RAG, analytics and ML can trust and reuse.
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