Services / Data Engineering & Analytics
Reliable pipelines, dashboards, reporting, and forecasting. We connect the systems that hold your data, make it consistent, and put it in front of the people who need it, so decisions stop waiting on a spreadsheet.
One version of the truth
Every department reporting the same number for the same thing
Built for reliability
Pipelines that run every day without someone babysitting them
Decisions, not exports
Dashboards designed around the questions leadership actually asks
Is this you?
By the time it is ready, nobody trusts it and the month is over.
Both are right about their system. Neither has the whole picture.
It is in the CRM, the ERP, and six spreadsheets, and none of them talk.
A forecast you do not believe is a chart, not a decision.
What we build
Data engineering is plumbing, and analytics is what you see at the tap. We build both, and we make sure they agree.
Reliable movement of data from the systems that create it to the place it is used, on a schedule or in real time.
One well-modeled store your reports, dashboards, and tools all read from, so the numbers match.
Validation, monitoring, and clear ownership so bad data is caught before it reaches a meeting.
Built around the decisions people make, not around what the data happens to contain.
Anomaly detection, trend forecasting, and outcome prediction your team can understand and check.
Find the gaps and risks hiding in your workflows by looking at what the data says is happening.
Where most work starts
Where your data lives, what state it is in, and what it would take to make it reliable. A plain report, not a platform pitch.
Every system that holds the data, and who depends on it.
Where the numbers conflict, go stale, or go missing.
The pipelines, model, and first dashboards to build, scoped and staged.
What changes
Before A week to assemble, then questioned in the meeting
After Ready when the meeting is, and trusted when it arrives
Before Sales and finance each bring their own figure
After One number per metric, so the debate is about what to do
Before Built by hand and rarely acted on
After Grounded in your data, explained plainly, reliable enough to plan around
Proof
Hearts for Hearing · Data & Modeling
A five-step data pipeline: merge, label, measure, average by demographic, generate. Plus a labeling application and a local Windows tool the clinical team runs on site. Data engineering in service of care.
How it runs
We map where your data lives, who uses it, and which questions it needs to answer. The gaps and conflicts show up fast.
We build the pipelines, the model, and the dashboards, and test them against the numbers your team already trusts.
Continuous Care monitors the pipelines, handles source changes, and keeps the reporting current as the business grows.
What to expect
Data projects sprawl if they are not scoped. We start with the three questions you most need answered and build outward from there.
Book a data assessmentQuestions we get
The tool is usually fine. The problem is upstream: inconsistent data, missing definitions, and no single place it all lands. We sort out the plumbing so the tool you have shows numbers people trust.
Not always. What you need is one well-modeled place your reports and tools read from, so the numbers match. The data assessment tells you what that should be, scoped and staged.
Governance is part of the build: validation, monitoring, and clear ownership. The assessment maps every system that holds the data and who depends on it, so you know what is sensitive before anything moves.
Yes. A single source of truth that is validated and monitored is what AI features need to run on. We also build AI into software, so the next step does not start from scratch.
YOUR NEXT DECISION
Tell us what's slowing you down, what you've tried, and what needs to be different. We'll start there.
Come with a problem. You don't need a specification.
The first conversation helps define the next step, whether or not that step is with us.