Data & Analytics that actually drive value, at any stage of your journey
We design and deliver modern data solutions, from analytics enablement to ETL development, governance and full data warehouse implementations, with a lean, local team. We're tech-stack agnostic, outcome-obsessed, and allergic to endless PM overhead.
Why Us?
Tech-stack agnostic.
Outcome over theatre.
Lean, capital-efficient delivery.
Local talent only.
End-to-end maturity support.
Service Pillars
Analytics & BI Enablement
For organizations and teams that are: Drowning in data but starving for insights. Whether your existing reporting is incomplete, inaccurate or too slow, or if you're looking to take the leap and implement a BI visualization tool, we can help you.
Assess your current reporting landscape, with measurable opportunities
Build semantic models / star-schema warehouses for tools like Power BI, Tableau, or Looker
Design and implement executive dashboards and domain-specific analytics (finance, operations, sales, HR, clinical/healthcare, etc.), including advanced functionality such as app embedding and RLS
Enable self-serve analytics without compromising security and governance
Fix or refactor existing reports/models that are slow, fragile, or opaque
Lead knowledge transfer & coaching sessions with your BI team to impart data modeling/visualization best practices
Data Platform Modernization/Implementation
For organizations and teams that are: Overdue an upgrade to a modern data strategy with better reliability and scalability, but wrestling with the mountain of options.
Assess your current SQL Server / ETL / reporting landscape
Design a modern architecture in your cloud of choice (Azure, AWS, GCP)
Implement data platforms like Microsoft Fabric, Snowflake, or Azure Synapse/Databricks
Plan and execute migrations from on-prem to cloud with minimal downtime
Optimize cost and performance (storage vs compute, tiering, scheduling, etc.)
Guide you through vendor/platform selection
Data Engineering & Ingestion
For organizations and teams that are: Struggling with blind spots in their data visibility, with complex SaaS/ERP platforms that need to be wrangled so their data can be utilized.
Ingest data from ERP/CRM/HRIS, custom apps, and third-party APIs
Build robust ETL/ELT pipelines using tools like Fabric Dataflows, ADF/Synapse, dbt, or custom Python
Standardize and model data for analytics and data science
Implement monitoring, alerting, and error handling so the pipelines keep flowing when we're gone
Set up CI/CD and deployment patterns appropriate to your size and maturity
AI Preparedness
For organizations and teams that are: Getting ready or looking to get ready for the AI wave.
Evaluate readiness (current state of the data environment)
Assess & propose use cases based on the data available, so you focus your efforts on impactful and realistic implementations, rather than a wild goose chase
Data modeling/preparation for use by modern data science techniques and libraries
Proof-of-concept implementations on concrete machine-learning use cases, for any audience
