We build enterprise data lakes, real-time streaming pipelines, and governed analytics platforms that turn raw data into a competitive advantage — without the runaway infrastructure bill.
Most teams have more data than ever — and less confidence in it than ever. The gap between data collected and decisions made is costing you more than you think.
Each team hoards its own database, spreadsheet, or SaaS export. Analytics requires three Slack threads, two Jira tickets, and a prayer that someone still knows the schema.
Your overnight ETL job means yesterday's numbers drive today's decisions. By the time the dashboard refreshes, the opportunity window has already closed.
Raw data dumped into S3 with zero governance. Duplicate tables, stale snapshots, and terabytes of data no one queries — all charged at full price every month.
Finance, product, and engineering all pull different numbers for the same metric. Every board meeting starts with a 20-minute debate about which spreadsheet is correct.
We don't install off-the-shelf tooling and leave. We architect a data platform your engineers understand, your analysts trust, and your finance team can actually explain to the board.
Event-driven ingestion from every source into a unified, queryable lakehouse. Sub-second latency from producer to analyst dashboard, with full ACID guarantees.
Scalable batch processing for historical backfills, heavy transformations, and data warehouse loads. Fully orchestrated, idempotent, and cost-optimised on spot capacity.
Stateful stream processing for fraud detection, real-time personalisation, live dashboards, and operational metrics that update as events happen — not the next morning.
Automated schema discovery, data lineage tracking, quality checks, and a self-service data catalog so every analyst knows exactly what data exists and whether to trust it.
We pick tools your team can own long-term — based on operational maturity, total cost of ownership, and community backing. No vendor lock-in by default.
Twelve weeks from kick-off to a production data platform your team fully owns. No vendor dependency. Complete documentation and knowledge transfer included.
Audit all data sources, query patterns, and current pipelines. Define platform north star, data contracts, and target architecture.
Build the lakehouse foundation, ingestion pipelines, transformation layer (dbt), streaming jobs, and governance catalog in parallel sprints.
Load testing, data quality validation, runbooks, on-call playbooks, and full hands-on knowledge transfer to your data engineering team.
Their data lived in six disconnected databases, two third-party SaaS tools, and a growing pile of manual CSV exports. Risk and compliance teams couldn't reconcile daily transaction summaries. Leadership was flying blind on key growth metrics.
We designed and delivered a real-time lakehouse on AWS — Kafka for ingestion, Glue + Iceberg for the storage layer, Redshift Serverless for analytics queries, and dbt for governed transformations. Twelve mission-critical pipelines replaced manual exports. Query latency dropped from 3 weeks to sub-second.
Read the full case studyNo surprise invoices. No scope creep. Every engagement starts with a clear deliverable and a fixed or range price.
Start with a free 30-minute data assessment. We'll map your current state and show you exactly where data friction is costing you the most.
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