BI · Data engineering · Automation

Your business deserves more than a spreadsheet.

We connect your data, automate repetitive work, and build reporting tools that make your team's job easier.

Led by Jeremy Dempsey, with about 20 years of BI experience. Backed by a team of developers ready to turn the plan into working tools.Led by Jeremy Dempsey, with about 20 years of BI experience, and a team of developers.

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Level 01 / See

All those sources. One clear picture.

Spreadsheets, downloads and databases connected into one reliable view, so every report starts from the same numbers.

Level 02 / Understand

Find the story inside the numbers.

When a week spikes, you find out whether something really changed or the reporting did. Here, week five is records counted twice.

Level 03 / Act

Know your next move.

The spike was 61 duplicate records. The fix is validation at the source, then a rebuilt history you can trust.

Level 04 / Predict

See beyond the next step.

Corrected history is the base for planning: illustrative higher, base and lower scenarios, with the assumptions in the open. This is the planning problem PredictNext is designed for.

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The method, on one example

Why two reports disagree, and what fixing it looks like.

An illustrative scenario with fictional numbers. The CRM export counts 1,284 new accounts in March; the finance workbook counts 1,197. They disagree for two different reasons, and only one of them is an error.

1,284 reported, minus 61 duplicate records, minus 26 accounts outside the finance cutoff, equals 1,197 comparable records. Fictional data.

1 · Duplicates are an error

A lead re-import created 61 accounts that already existed, so the CRM counted them twice. That is a data-quality defect, and the fix is a validation rule at the source.

2 · The cutoff is a definition

26 accounts opened on March 31, after the finance cutoff. Neither system is wrong here; they count different periods. The fix is one written definition of "new account in March".

3 · One source, one check

Both reports now read from the same organized table. A check compares the two counts every morning and flags any gap, so the next disagreement is caught before a meeting.

4 · What it enables

Reconciled history is a starting point for planning, not a forecast in itself. A forecast still needs assumptions and a range of outcomes.

Products

Plan your next move. Put AI to work.

Illustrative data

PredictNext

See what's ahead. Plan your next move.

Forecasting and budgeting together, so you can look ahead, question your assumptions, and make more informed planning decisions.

Explore PredictNext

ByteBoost.ai

Your team has more important work to do.

An AI-agent tool for businesses. Start with the work you want help with.

Explore ByteBoost.ai

How we work

Listen first. Then find the real problem.

  1. Listen

    What do you need to know, who needs it, and how is it produced today?

  2. Investigate

    Trace the sources, the manual steps and the places where numbers stop matching.

  3. Solve

    Build the practical version: organized data, automated refresh, clear visuals.

  4. Support

    Document it, hand it over, and stay available as the questions change.

Training

Hands-on BI and Tableau training in Orlando.

Public small-group workshops are being developed for up to eight participants, with time to practice and ask questions. Corporate training is a separate offering, with group size agreed with you.

Dates, pricing, venue and curriculum are still in development. Send an inquiry from the contact page to hear when the first dates are set.

Ready when you are

What would you like your data to help you do?

Tell us what is difficult today, whether it is a report, a manual process, or a bigger planning problem. A short conversation helps us understand the problem and agree on a useful next step.