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SolutionsData Modernisation

Infinite scale.
Zero management.

Move beyond rigid data warehouses. We architect intelligent Serverless Data Platforms on AWS that scale automatically and are designed to lower the cost of running analytics.

Low-Cost Storage Tier
S3
Servers to Manage
0
Scale Analytics
Petabyte

Instant Insights

From lagging indicators to leading insights.

Stop driving with the rear-view mirror. Legacy batch jobs leave you 24 hours behind. Our serverless pipelines deliver data the moment it happens, enabling faster decision-making and automated reactions.

Real-Time Availability

Data is available for query seconds after ingestion.

Self-Healing Infrastructure

Pipelines automatically retry and recover from failures so you don’t wake up to broken jobs.

Pay-per-Event Economics

Stop over-provisioning. Pay only for the data you process, when you process it.

Legacy

Batch Bottleneck

  • 24h+ Data Latency
  • Siloed Adjustments
  • Idle Resource Cost
Modern

Real-Time DataOps

  • 24ms Latency
  • Unified Stream
  • Pay-per-Event

The AWS serverless stack.

Fully managed. Integrated. Secure.

Automated ETL

Intelligent Ingestion with AWS Glue

Forget writing fragile scripts. We deploy AWS Glue to crawl, catalogue, and transform your data automatically. It builds a unified metadata layer so you know exactly what data you have, making it instantly searchable.

AWS Glue Architecture
Zero-Wait BI

Instant Analytics with Amazon Athena

Need answers now? Amazon Athena lets you run standard SQL queries directly against your raw data in S3. No loading, no clusters, just results. Perfect for ad-hoc exploration and data discovery.

Amazon Athena Querying
Enterprise Scale

High-Performance with Redshift Serverless

For complex dashboards and reporting, Redshift Serverless provides the fastest cloud data warehouse performance without you ever provisioning a single node. Scale from GBs to PBs seamlessly.

Amazon Redshift Serverless Dashboard

Our methodology.

A proven path to data maturity.

  1. Step 01

    Design & Secure

    We define the Lake House architecture, implementing AWS Lake Formation for fine-grained row/column security and governance compliant with GDPR/CCPA.

  2. Step 02

    Ingest & Catalogue

    We build automated Glue pipelines to ingest data from on-prem DBs and SaaS APIs. The Data Catalog ensures your data is discoverable and structured.

  3. Step 03

    Analyse & Innovate

    We set up Athena/Redshift for BI teams and SageMaker for Data Scientists to consume the clean data, driving real business innovation.

Typical use cases.

Typical Use Cases
SectorUse CaseApproach
Retail360-degree customer viewUnified analytics layer
FinTechReal-time fraud detectionStreaming analytics
ManufacturingIoT sensor analysisPredictive maintenance

Next step

Unleash your data.

Stop paying for idle clusters. Start building a data platform that scales with your ambition.

A 30-minute peer conversation, not a sales pitch.