Businesses are drowning in data and thirsty for decisions. We help you build the foundations – data quality, architecture, governance, and the analytics that actually get used.
Most businesses have more data than they know what to do with. It's spread across SaaS tools, spreadsheets, databases, and files – inconsistent, poorly defined, and hard to query. The dashboards that exist either aren't trusted or aren't looked at.
In media production and post-production, data problems manifest as: no reliable project cost tracking, no view of resource utilisation across productions, asset metadata that's inconsistent across systems, and financial reporting that requires someone to stitch together three spreadsheets manually every month.
The answer isn't always a bigger data platform. It's usually clearer definitions, better pipelines, and reporting that answers the questions the business actually has.
Customer, financial, and operational data spread across disconnected systems with no single source of truth.
Different teams produce different numbers for the same metric. Nobody knows which one is right, so decisions get made on instinct.
Data lakes and warehouses built for scale that doesn't exist yet – expensive to maintain, hard to use, and not answering the core questions.
We start with what decisions you need to make, work backwards to the data that answers them, and build the simplest infrastructure that delivers it reliably. No unnecessary complexity.
What data matters for your business decisions, how it should be structured, and what investment is proportionate to the value it delivers.
Warehouse, lakehouse, or something simpler – we design data infrastructure that fits your volume, team, and query patterns without over-engineering.
Definitions, ownership, quality rules, and access controls. The boring stuff that makes everything else reliable.
Dashboards and reports that get used – built around real decisions, with consistent metrics, and designed for the people who need to act on them.
ETL/ELT pipelines that move data reliably between systems – built with appropriate tooling, monitored, and documented.
For M&E clients: production cost tracking, asset metadata standardisation, resource utilisation across productions, and MAM/DAM integration.
We start with the business questions that matter most – what decisions need better data? What's being guessed that shouldn't be? This shapes everything that follows.
We map your data landscape – what exists, where it lives, how it's defined, and how reliable it is. We identify gaps, quality issues, and integration opportunities.
We design the data infrastructure and tooling that fits your scale and team – and sequence the work so you get value early, not at the end of a long build.
Pipelines, transformations, models, and reporting – built incrementally with testing and documentation. We validate that outputs match expected values before anything goes to production.
We make sure the outputs are actually used – training, feedback loops, and ongoing refinement based on how the business uses the data in practice.
Tell us what decisions you're struggling to make and what data you have. We'll figure out the gap together.