Data warehouse and lakehouse implementation, ETL/ELT pipelines, real-time streaming, data governance, and data migration — the foundational data platform your analytics and AI depend on.
Most organisations have more data than ever — and less confidence in it. These are the infrastructure and governance problems we solve before any BI tool or ML model can deliver value.
Operational data locked in CRMs, ERPs, and spreadsheets — no single source of truth for reporting or ML.
Overnight batch runs mean dashboards are 12–24 hours behind. Leaders make decisions on yesterday's numbers.
Brittle ETL scripts break on schema changes. Data quality issues silently corrupt reports with no alerting.
No data lineage, uncontrolled PII sprawl, and undocumented datasets that block GDPR, HIPAA, and audit readiness.
Legacy warehouses billed on compute × storage. Teams hit query timeouts and pay for capacity they don't need.
Business stakeholders queue behind the data team for every report. Self-service is a goal, not a reality.
We build data platforms using the medallion architecture — Bronze (raw ingest), Silver (cleaned and conformed), Gold (business-ready aggregates). This layered model gives you a single source of truth that serves BI dashboards, operational APIs, and ML training data from the same governed platform.
Every pipeline we build is version-controlled, tested, and documented — using dbt for transformation, Airflow or Prefect for orchestration, and Great Expectations or Elementary for data quality. You inherit production-grade infrastructure, not scripts that only the original engineer can understand.
The full stack — from raw ingestion to analytics-ready data products — built to scale and operate without a dedicated data infrastructure team.
Snowflake, BigQuery, Redshift, and Databricks implementations — dimensional modelling, medallion architecture (Bronze/Silver/Gold), and data vault design for analytics-ready, AI-ready data.
dbt, Apache Spark, Airflow, and Fivetran-based pipelines — batch and micro-batch ingestion, transformation, and loading from operational systems at any scale with full lineage tracking.
Kafka, Flink, and Kinesis streaming pipelines for real-time event ingestion, CDC from operational databases, and stream processing for live dashboards and operational alerts.
Data catalogues (Datahub, OpenMetadata), lineage tracking, schema registries, Great Expectations quality checks, and PII classification and masking for compliance.
Migrate from legacy data warehouses, on-premise databases, and siloed data marts to modern cloud platforms — with zero data loss, validated parity, and rollback capability.
CI/CD for data pipelines, automated testing, Monte Carlo or Elementary for data observability, SLA alerting, and on-call runbooks so you catch issues before stakeholders do.
A phased delivery model that delivers working pipelines early — so your team gets value while the full platform is still being built.
Audit existing data sources, schemas, volumes, and quality. Map data flows and identify gaps in governance and infrastructure.
Design target state — warehouse topology, medallion layers, pipeline patterns, streaming vs batch decisions, and governance model.
Provision cloud infrastructure, implement core pipelines for priority data domains, and establish dbt project structure and coding standards.
Deploy data catalogue, implement quality checks, set up lineage tracking, PII tagging, and access control policies.
Onboard remaining data sources, tune query performance and compute costs, and enable self-service access for analytics teams.
DataOps handover — CI/CD for pipelines, observability dashboards, runbooks, and optional ongoing managed operations.
We work with the tools your team already knows — or recommend the right fit for your workload, team size, and budget. No vendor lock-in.
Warehouses & Lakehouses
Orchestration
Transformation
Ingestion
Streaming
Governance
From e-commerce to healthcare and manufacturing — data platform patterns that work across verticals, deployed across India, UAE, USA, Europe, and Australia.
Unified lakehouse ingesting Shopify, Google Ads, and Klaviyo — daily revenue, CAC, LTV, and cohort dashboards delivered to 200+ business users via Looker.
HIPAA-compliant Snowflake warehouse aggregating EHR, billing, and claims data — anonymised ML-ready datasets for readmission prediction models.
Real-time P&L and regulatory reporting pipeline replacing a legacy on-premise Oracle warehouse — 12× query performance improvement, 40% cost reduction.
Kafka streaming pipeline ingesting 50M sensor events/day from production lines — real-time OEE dashboards and anomaly detection reducing downtime by 23%.
Certified across Snowflake, Databricks, BigQuery, and Redshift — we recommend what fits your workload and budget, not what we're vendor-incentivised to sell.
Teams in India, UAE, USA, Europe, and Australia with timezone coverage that keeps your build moving across time zones.
All transformation logic in version-controlled dbt — documented, tested, and reproducible. Your team inherits production-grade code, not black-box ETL.
GDPR, HIPAA, SOC 2, and UAE data residency requirements addressed at the architecture layer — not retrofitted after deployment.
We build platforms that serve BI today and ML tomorrow — medallion layers, feature stores, and governance that your data scientists will thank you for.
