Skip to content

Data. Models. Systems.

Intelligence
in the details.

We turn complex data and business logic into models, automation, and software you can put to work.

Discuss your project Explore the work

Statistical rigor.
Practical engineering.

Scroll to explore ↓

The useful connections

Your business has its own logic.
Your systems should reflect it.

Pricing rules. Forecast assumptions. Exceptions buried in a workbook. We work through the details with you, then build the models and software that connect them.

What we build

From underlying data
to everyday decisions.

All capabilities
01

Give your data a foundation.

Connect sources, reconcile definitions, and automate the path from raw inputs to reliable datasets.

Data pipelines · Quality checks · Workflow automation
02

Model what matters.

Forecast, allocate, and explore scenarios with statistical methods that respect your business constraints.

Forecasting · Distribution modeling · Optimization
03

Put intelligence to work.

Build custom applications, integrations, and AI workflows around the way your team actually operates.

AI systems · Internal tools · Custom software

How we work

Close to the problem.
Accountable for the build.

We work directly with your team, inside your data and systems. The engagement follows the problem—from understanding the inputs to building, validating, and handing over a working solution.

Our approach to embedded engineering
Defined scopeVisible progressDocumented handover

Selected work / Market intelligence

From conflicting inputs
to a forecast teams can use.

Take a look at a current market intelligence engagement: we turned fragmented country, vendor, and price data into a repeatable forecasting workflow with explicit constraints, diagnostics, and reviewable outputs.

The problem

Country, vendor, and regional totals did not always agree, while tier rules, historical records, and quarterly targets still had to remain consistent.

The build

We engineered a Python allocator and command-line runner that models price distributions, preserves applicable unit and revenue constraints, and produces datasets plus an Excel review workbook.

The impact

The client gets a repeatable, inspectable planning workflow with less manual assembly, clearer exceptions, and evidence that makes the forecast easier to review and act on.

Inside the project
Market intelligence workflowCurrent engagement
01 / INPUTS02 / ENGINE03 / OUTPUTSource dataCountry totalsVendor viewsUnits + revenueHistorical recordsConstrained modelDistributions · rules · checksDecision-readyTier forecastsReconciled workbookException reportsReviewable evidence
Inputs → constraints → evidenceAssumptions made explicit

Technical leadership

Daniel Carrillo

CTO, Niche Intelligence

Technical depth. Close to the business.

From statistical models to the software around them, Daniel brings the business question and the engineering details into the same conversation.

Meet our CTO

Start a conversation

Let’s work through the details.

Tell us about the data, the decision, or the workflow you want to improve. We’ll start there.

Discuss your project