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Data and analytics

Make the operating truth easier to see and act on.

A dashboard is only the visible layer. We build the definitions, integrations, models, pipelines, permissions, and interfaces required to make analytics trustworthy in day-to-day decisions.

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Business outcomes

What the work can change.

  • 01Unify fragmented reporting and source systems
  • 02Connect marketing, operations, and finance
  • 03Build analytics directly into a product
  • 04Give teams one defensible definition of performance
Delivery

How engineering moves the work.

  1. 1Map decisions, source systems, and metric ownership
  2. 2Design the data model and quality rules
  3. 3Build pipelines and decision-ready interfaces
  4. 4Monitor freshness, adoption, and definition drift
Representative work

Proof in production context.

Product engineering / Growth engineering

Local discovery website and publishing engine

A custom-designed, data-backed website that turns live community information into useful, crawlable city and event resources.

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Applied machine learning

ZIP-code lead prioritization

A regression system using public demographic data to help a home-services call center prioritize incoming leads.

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Applied machine learning

Commodity demand forecasting

A multi-model supply-and-demand forecasting system for one of the country’s leading avocado suppliers, evaluated against real purchasing decisions.

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Start with the real problem

Talk directly with an engineer who can help build it.

Bring the current system, the desired outcome, and whatever uncertainty remains. We will help identify the smallest credible path to production.

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