Services / Analytics & Intelligence

Data you can see.
Insight you can act on.

Most dashboards answer questions nobody asked. We build analytics systems that answer the questions your business actually runs on — designed around decision-making workflows, not data availability.


Capabilities

What we build.

BI & Dashboard Engineering

Looker, Metabase, Apache Superset, Power BI, Tableau — not just configured, but semantically modelled. Metrics that mean the same thing on every dashboard, to every team, every time they're queried.

Semantic Layer Development

A single, governed definitions layer for your business metrics. One authoritative source for revenue, retention, CAC, LTV, and every other number that shows up in a board meeting. Built on dbt metrics, Cube.dev, or LookML.

Self-Serve Analytics Enablement

Data infrastructure and tooling that empowers non-technical teams to answer their own questions — without submitting requests to a data team that's already at capacity.

Product Analytics Infrastructure

Mixpanel, Amplitude, Segment, PostHog — full-funnel instrumentation, event taxonomy design, and behavioural analytics systems. Understand what your users are actually doing, not what you assumed they were doing.

Predictive & ML Infrastructure

Feature stores, ML pipeline infrastructure, and model serving layers. We build the data and compute infrastructure that puts ML models into production — not just into notebooks.

Executive & Investor Reporting

Board-ready, investor-grade reporting infrastructure. Automated, auditable, accurate, and explainable — because the CFO and the investor both need to trust the same number.


Use cases

Teams we've helped.

01

CEO making critical business decisions from three dashboards showing three different revenue figures — unified into a single semantic layer with one authoritative metric definition.

02

Product team with rich event data but no coherent funnel visibility — instrumented from scratch, modelled in dbt, and surfaced in a self-serve Metabase instance.

03

Operations team spending 40% of analyst capacity on manual data preparation — automated through a governed ELT pipeline and semantic layer.

04

Retail company building predictive inventory models — we built the feature store, training pipeline, and batch inference infrastructure.

05

Growth team unable to accurately attribute CAC across six acquisition channels — we built a multi-touch attribution pipeline that gave them channel-level ROI visibility for the first time.

06

Pre-IPO company requiring investor-grade financial reporting with full auditability and automated reconciliation across ERP, CRM, and billing systems.


Platforms & tools

dbt MetricsCube.devLookMLLookerMetabaseApache SupersetPower BITableauMixpanelAmplitudeSegmentPostHogFeastMLflowVertex AI PipelinesSageMaker Pipelines

Ready to talk about your infrastructure?

Every engagement starts with a discovery phase — no obligation. We map your current state and give you a concrete roadmap before you commit to anything.

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