Rowvyn

    Data Integration & Reporting

    Connect your business data. Get numbers your team can trust.

    Rowvyn builds data pipelines, dashboards, and reports around the decisions your business needs to make. Start with the question and trace it back to the source.

    Sales, accounting, stock, and operational records only become useful together when the definitions and connections make sense.

    Connected
    records from the systems that matter
    Defined
    metrics with a clear business meaning
    Checked
    outputs reconciled to appropriate sources

    The operating problem

    What starts breaking first.

    Reliable reporting needs a clear question, usable source data, and agreed definitions. A new dashboard alone cannot repair a broken join or an unclear metric.

    Reports disagree and nobody knows which one to use

    A weekly report requires repeated exports and spreadsheet work

    Sales and financial data are difficult to compare

    Important decisions depend on a number the team cannot easily see

    The build

    What Rowvyn puts in its place.

    We follow the data from source to decision, resolve the differences, and build views your team can use. Refresh frequency and source limitations are made explicit.

    Connections between operational, sales, and finance data

    Data pipelines with an agreed refresh and failure-checking process

    Dashboards and reports for actual operating decisions

    Metric definitions, reconciliation checks, and maintenance documentation

    The process

    A practical build, in the right order.

    The sequence is simple on purpose. We inspect the operation, choose the highest-leverage move, ship it, and make sure the team can use it.

    1. 01

      Define the question

      Agree what the team needs to decide and how each important metric should be calculated.

    2. 02

      Connect the sources

      Check access, exports or APIs, record identifiers, history, and refresh requirements.

    3. 03

      Build and reconcile

      Create the pipeline and views, then compare representative results with the appropriate source reports.

    4. 04

      Document the operation

      Record definitions, refresh behavior, exceptions, and who handles ongoing maintenance.

    Proof from the field

    For an HVAC client, Rowvyn built a ServiceTitan-to-BigQuery reporting foundation that surfaced $1.3M–$2.1M in unsold estimate value and made a 46% close rate visible. Pipeline identified is distinct from revenue recovered.

    Read the HVAC data case study
    $1.3M–2.1M
    unsold estimate value identified
    46%
    existing close rate made visible
    Source-checked
    representative revenue reporting reconciled

    Before we start

    A clear scope, from the first conversation.

    These are the questions worth settling before a project becomes a build.

    Read a practical starting guideUnderstand ownership and running costsExplore business applications
    What happens before a build starts?

    We inspect the workflow, the people using it, and the available systems. If custom work is a fit, the proposal sets out deliverables, boundaries, acceptance checks, estimate, timeline assumptions, and responsibilities.

    Can you work with the software we already use?

    Often, yes. We check the specific tools, account permissions, APIs or exports, and data quality before committing to an integration. Sometimes configuration or an existing product is the useful first step.

    What changes the cost and timeline?

    The number of workflows, integrations, users, exceptions, and access constraints all matter. Data cleanup, review requirements, and the agreed support/handoff also affect scope. We estimate the actual job rather than publish a generic delivery promise.

    Who owns the code, accounts, and data?

    The project agreement defines client-specific code, existing components, account control, and data ownership. Third-party services retain their own terms. The handoff should make the dependencies and access responsibilities clear.

    What does it cost to keep the result running?

    Hosting, storage, provider usage, maintenance, and support can remain ongoing costs. The proposal separates the build from operating assumptions and any agreed support. Owning a tool gives you control over those decisions.

    How do you handle business data and AI access?

    We define which data the task needs, who can authorize access, and which providers are appropriate for the project. Review and approval boundaries depend on the sensitivity of the information and the consequence of an incorrect result.

    What happens after launch?

    Documentation, operating responsibilities, training, and any maintenance or support are defined in the scope. Your team should know how the system runs, what its limitations are, and who handles an exception.

    Start with the bottleneck

    Let's figure out what you actually need.

    Bring the number you need, the reports that disagree, or the export someone rebuilds every week. We'll inspect what the sources can support.

    Talk through your reporting problemReview the case studies