Built for real production load
Six engineering pillars, each with shipped reference implementations available on request.
Data Warehouse & Lakehouse
Snowflake, BigQuery, Redshift, and Databricks Lakehouse architectures optimized for query speed and cost.
ETL / ELT Pipelines
dbt + Airbyte/Fivetran pipelines unifying 50+ data sources with sub-hour latency and full lineage tracking.
BI & Executive Dashboards
Looker, Power BI, Tableau, and custom React dashboards with drill-down, alerts, and embedded analytics.
Predictive ML Models
Churn prediction, demand forecasting, fraud detection, LTV modelling — built in Python and deployed via MLOps.
Real-Time Data Streaming
Kafka, Kinesis, and Flink-based streaming pipelines for live dashboards, fraud detection, and IoT telemetry.
AIOps & Intelligent Monitoring
ML-driven observability that detects anomalies, predicts incidents, and reduces alert fatigue by 80%.
Faster executive decisions enabled by real-time dashboards vs. weekly spreadsheet reports.
Average revenue uplift attributed to data-driven pricing, segmentation, and retention strategies.
Data accuracy and freshness SLA achieved after our governance and pipeline standardization programs.
From main to mainstream
Data Audit & Strategy
Map all data sources, assess quality, and identify the top 5 high-value analytics use cases by ROI.
Stack Design & Setup
Select and provision your modern data stack: ingestion, warehouse, transformation, BI — all infrastructure-as-code.
Build & Ship Dashboards
Migrate historical data, build pipelines and models, and deliver first executive dashboards within 4 weeks.
Enable & Govern
Self-serve onboarding, data dictionaries, governance, and ongoing support to make your team data-independent.
