We engineer the plumbing every data-driven business needs: ingestion you can trust, transformations you can debug, and warehouses your analysts will actually query. No leaky pipelines, no "dashboard graveyard," no shadow ETL.
Five capabilities, each shaped by years of plumbing real systems at real scale. Pick the closest to your bottleneck — we'll bring the rest as the work demands.
Dashboards your CFO opens daily, metrics layers that survive a re-org, and self-serve BI that doesn't need a translator.
metrics · BI · self-serveClean ingestion, dimensional modeling, governed warehouses on Snowflake / Redshift / BigQuery. Built to outlast your tooling.
ingest · model · warehouseRaw-to-curated layers on Delta / Iceberg with ACID semantics, time travel, and unified batch + streaming. One source of truth, finally.
delta · iceberg · medallionPetabyte-scale Spark, sub-second Kafka / Flink stream processing, lambda + kappa architectures that earn their complexity.
spark · kafka · flinkLabeled datasets for training and eval — text, audio, image, video. Domain-expert reviewers, double-blind QA, edge-case sweeps.
label · review · auditThree lanes, one team. Move freely across foundations, modeling and activation — no "data team backlog" theater.
Source connectors, change-data-capture, schema evolution, and the boring observability that keeps you off the on-call pager.
dbt-led transformations, dimensional and one-big-table where each earns its keep, semantic layers that anchor every dashboard.
Reverse-ETL into the tools sales and ops actually use, BI dashboards leaders trust, governance that satisfies legal without strangling speed.
We choose tools that survive vendor drift — open table formats, OSS engines, data catalog layers. So your platform outlasts the hype cycle that built it.
Every industry generates data faster than it can absorb. We've built the absorbing layer for seven of them.
Real-time fraud signal pipelines, regulatory reporting marts, and ledger-grade reconciliation across exchanges, custodians and counterparties.
Learner-event streaming at scale, cohort analytics that survive a curriculum rewrite, and the longitudinal datasets ML actually needs.
HIPAA-compliant clinical data lakes, EHR integrations, and ML-ready feature stores for diagnostics and population health.
Unified customer view across stores, app and ad networks, inventory-grade SKU tables, and reverse-ETL into the merch tools.
Product analytics warehouses, usage-based billing pipelines, and the activation tooling that lets marketing actually fire.
IoT & telematics ingestion, geo-indexed warehouses, and ML-ready features for routing, demand and exception management.
No 200-page proposals, no "phase 0" theater. A working pipeline in your hands inside six weeks — then we iterate in public.
Stakeholder workshop, opportunity matrix, success metrics agreed in writing.
Audit existing data, design ingestion strategy, scope the v1.
Working pipeline with real data, evaluated against agreed metrics. Real, not Figma.
Harden the system — quality tests, monitoring, infra-as-code. Ship behind a flag.
Drift watch, weekly quality checks, quarterly optimization, business-outcome reviews.
Anonymized where contracts require, but every number is in our quarterly close. Ask in the call and we'll walk you through the build.
From fragmented data sources to a unified operational dashboard. Reduced close time from 7 days to 4 hours.
Real-time inventory pipeline across 1,800 stores, 3 DCs, and 7 supplier EDI feeds.
From scattered FHIR feeds and CSV dumps to a governed medallion architecture with full auditability.
Book a 30-minute data audit. We'll either map a clear path to a working data platform — or tell you, honestly, where to start before the platform.