Breadcrumb Analytics

Solve the data problems holding your work back.

Breadcrumb connects fragmented data, repairs unreliable workflows, and builds practical AI solutions. We help your team turn difficult data into usable results, with a clear record of where those results came from.

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How we can help

Start with one concrete problem

Data & AI Architecture Assessment

Know what to fix before committing to a build. We review your data sources, systems and goals, identify the main obstacles, and deliver a prioritized plan with a clearly scoped next step.

You receive: a current-system map, prioritized issues, recommended architecture and a scoped implementation plan.

Data Integration & Rescue Sprint

Get a stalled workflow moving. We connect sources, resolve data inconsistencies, and repair the processing steps behind one agreed business or research workflow.

You receive: a connected or repaired workflow, validation checks and documentation your team can use.

AI Proof-of-Concept Sprint

Test a specific use case with your data. We build a focused prototype, evaluate it against agreed criteria, and explain its limitations and what it would take to move into production.

You receive: a working prototype, evaluation results and a recommendation on next steps.

Selected experience

Experience you can examine

Healthcare research data

Breadcrumb supported data management for University at Buffalo research on hepatitis C and social determinants of health. The related PCORI-funded telemedicine trial received a 2025 Top Ten Clinical Research Achievement Award.

Read the UB news story

Integration of incomplete and inconsistent data

Breadcrumb is a collaborator on CURE-C, a NASA-funded STTR Phase II project developing tools to help analysts integrate incomplete, inconsistent and uncertain data.

Read the University at Buffalo project announcement

Our approach

Understand how the result was produced

We build workflows that preserve the connection between source data, processing steps and outputs. That makes it easier to investigate discrepancies, repeat an analysis and understand what changed.

A clear scope before work begins

We start by understanding the problem, the available data and what a useful result would look like. Then we agree on deliverables, responsibilities, timing and cost.