One trusted view of your business, refreshed automatically.
We build the pipelines, warehouse, and dashboards that turn scattered store, sales, and finance data into reliable numbers leaders act on.
When to bring us in
- Every report starts with exporting spreadsheets from several systems
- Departments argue about whose numbers are right
- You want AI or forecasting but your data is not ready
- Dashboards are slow, stale, or nobody trusts them
Data Engineering & Analytics capabilities
Data Pipelines (ETL / ELT)
Automated ingestion from apps, databases, APIs, and files with quality checks.
Data Warehouse & Lakehouse
Modern cloud warehouses on Snowflake, BigQuery, Redshift, or PostgreSQL.
Data Modelling
Clean, documented business models for sales, inventory, finance, and customers.
BI Dashboards & Reporting
Executive and operational dashboards in Power BI, Looker, Metabase, or embedded in your apps.
Data Quality & Governance
Tests, lineage, access policies, and data catalogues.
Real-Time Analytics
Streaming pipelines for live operational metrics and alerts.
How a typical engagement runs.
- 01
Audit
Map sources, metrics definitions, and current reporting pain.
- 02
Model
Agree metric definitions and design the warehouse model.
- 03
Build
Pipelines, tests, and dashboards delivered in iterations.
- 04
Enable
Train users, document metrics, and set up ownership.
Tools and platforms we work with.
Warehouse
- Snowflake
- BigQuery
- Redshift
- PostgreSQL
Pipelines
- dbt
- Airflow
- Fivetran / Airbyte
- Kafka
BI
- Power BI
- Looker
- Metabase
- Embedded analytics
Languages
- SQL
- Python
What you receive
- Source-to-warehouse pipelines with data tests
- Documented metric definitions
- Executive and operational dashboards
- Data governance and access model
What changes for your business.
One version of the truth
Agreed metric definitions used across every report.
Hours back every week
Automated refreshes replace manual spreadsheet consolidation.
AI-ready data
Clean, modelled data is the foundation for forecasting and AI.
Work with us the way that fits your project.
Fixed-Scope Project
Best for: Well-defined requirements and a fixed budget
Dedicated Team
Best for: Ongoing product development
Time & Materials
Best for: Evolving scope and fast iteration
Managed Services
Best for: Systems already in production
Data Engineering & Analytics questions
Do we need a data warehouse to start?
Not always. For smaller data volumes we often start with a well-modelled PostgreSQL database and move to a dedicated warehouse when scale demands it.
Can dashboards be embedded in our own product?
Yes. We build embedded analytics with row-level security so each customer sees only their own data.
Often combined with
AI & Machine Learning
Generative AI assistants, RAG, AI agents, forecasting, and document automation in production.
Enterprise Integration & Legacy Modernization
Connect ERP, CRM, POS, and finance systems, and modernize legacy applications step by step.
Cloud & DevOps
Cloud migration, cloud-native architecture, CI/CD, Kubernetes, and infrastructure-as-code.
Let’s talk about your Data Engineering & Analytics needs.
Share your goals and constraints. A solutions architect will reply with questions, an approach, and next steps — no obligation.