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Automation · Business Intelligence · Data Architecture · Microsoft & Google · Southern Arizona

Your people are doing work that software should be doing.

Paying a salary to move data between spreadsheets is one of the most expensive habits a company can have. KADx builds the automations, dashboards, and data systems that end it — on Microsoft or Google, whichever your business already runs on — then hands the whole thing over to your team and gets out of the way.

Tucson · Nogales · Rio Rico · Sierra Vista · Marana · Green Valley · Remote nationwide

The math

What is that task actually costing you?

Not a quote — arithmetic. Put in the hours your team burns on one repetitive process and what that labor costs loaded. The number on the right is what you are already paying, every year, to not fix it.

12

Across everyone who touches it. Month-end counts — divide it by four.

$35

Wage plus payroll tax, benefits, and overhead — roughly 1.3× the hourly wage.

Most first engagements land in the middle.

You are spending, every year
$21,840

on one process that runs itself once it's built.

Cost over three years $65,520
One-time cost to automate it $7,500
Net savings in year one $14,340
Net savings over three years $58,020
Work-weeks returned to your team, per year 15.6

The build pays for itself in 18 weeks. After that it costs nothing and keeps working — which is the real answer to "can we afford this." You are already paying for it. You're just paying a person instead of paying once.

Straight arithmetic on the numbers you entered — no assumed efficiency multiplier, no soft benefits, no discount rate. Real engagements usually beat this, because eliminating the task also eliminates the errors, the rework, and the three-day delay in the answer.

Take it to the budget meeting

Download these numbers as a one-page PDF, a two-slide deck, or a working spreadsheet your finance team can check for themselves.

Capabilities

If it has a process, it can be automated.

A process is a repeatable sequence of decisions and actions — and anything repeatable can be handed to software. The only real question is whether the payback justifies the build, and we will tell you honestly when it doesn't.

We work in both ecosystems. Microsoft 365 and the Power Platform, or Google Workspace and Google Cloud — Power BI or Looker Studio, SQL Server, Snowflake, or BigQuery, Power Automate or Apps Script. We fit the stack you already own rather than selling you a migration you didn't ask for.

01

Intelligent automation & agentic AI

From the mundane to the genuinely advanced. Power Automate flows and Google Apps Script for approvals, routing, notifications, and scheduled exports — whichever platform your company lives in. UiPath RPA bots for systems with no API, where software has to drive the screen the way a person would. Python services for file handling, data traceability, document auditing, and anything that needs real logic. REST API integrations to make two systems talk that were never designed to.

And increasingly, agentic AI: assistants built in Copilot Studio that answer questions from your own documentation instead of making someone search for it, and LLM assistants embedded directly in a dashboard so a manager can ask "why was margin down in March?" in plain English and get a real answer back from millions of rows, built on LLM integrations and Snowflake Cortex.

Power AutomateGoogle Apps Script UiPath RPAPython Copilot StudioLLM integration REST APIsVBA / macros JavaScript
02

Business intelligence & dashboards

Dashboards built on a real semantic model — star schema, defined relationships, advanced DAX measures — not a pile of imported worksheets with a chart on top. The difference is whether the numbers reconcile, whether the refresh survives month-end, and whether anyone trusts it six months from now.

Power Query / M for transformation at the source. If you're a Google shop, the same discipline applies in Looker Studio on top of BigQuery or Connected Sheets — and Looker Studio itself is free, which often means the reporting layer costs you nothing at all. Tableau when that's already your standard. Predictive modeling and forecasting where the history supports it. Designed so a non-technical executive opens it on Monday and needs no training to understand what they're looking at.

Power BIAdvanced DAX Power Query / MLooker Studio Google SheetsTableau Semantic modelingPredictive modeling
03

Data architecture & warehousing

One source of truth instead of nine workbooks and three people's opinions. We design and build the layer underneath everything else: SQL Server warehouses, Snowflake data platforms, Microsoft Dataverse environments, Google BigQuery warehouses, and ETL pipelines that consolidate systems which were never meant to be consolidated.

That includes the unglamorous work that determines whether any of it holds up: relational data modeling, metadata standardization so a customer or a SKU means one thing everywhere, and data governance rules written down so it stays clean after we leave. We have migrated legacy SharePoint and spreadsheet-based reporting into scalable architecture handling 1.6 million+ row datasets.

SQL Server / SSMSBigQuery SnowflakeDataverseETL pipelines Relational modelingMetadata standardization Data governanceLegacy migration
04

EDI & trading-partner integration

If your customers send purchase orders electronically and somebody on your team still retypes them into a spreadsheet, you are paying twice for the same data. We map and onboard trading partners, reconcile 856 advance ship notices against what actually left the dock, and build the reporting that finally shows which retailer, which transaction type, and which SKU your chargebacks are coming from.

Most BI firms will not touch EDI. It is precisely where the money tends to be leaking.

850 / 855 PO856 ASN 810 / 820 invoicing852 activity Partner onboardingChargeback analytics
05

Performance engineering

The part most consultancies skip, because it requires actual computer science. Complexity analysis on the transformations, query folding so work happens at the source instead of on the desktop, and Table.Buffer logic applied where it helps rather than everywhere out of habit.

This is the difference between a dashboard that takes thirty seconds to load and one that responds instantly on a multi-million row model. It is also the difference between a refresh that quietly fails at month-end and one that doesn't.

On Google Cloud this goes straight to the invoice: BigQuery bills by how much data each query scans, so proper partitioning, clustering, and eliminating full-table scans don't just make reports faster — they cut the monthly bill. For a company with a poorly modeled warehouse, that saving alone can cover a meaningful share of the build.

Complexity analysisQuery folding Table.Buffer logicBigQuery partitioning ClusteringCost optimization Model tuning
06

Process engineering

Sometimes the honest answer is that the software isn't the problem — the process is. Lean Six Sigma methodology, root cause analysis, and value stream mapping to find where the friction actually lives before anyone spends money automating the wrong thing.

Automating a broken process just produces broken output faster. We would rather tell you that in the free hour than bill you for it.

Lean Six SigmaRoot cause analysis Value stream mappingSLA design Workflow redesign

Before you buy anything else

You are almost certainly already paying for most of this.

Whether your company runs on Microsoft 365 or Google Workspace, you are almost certainly using a fraction of what you already license. Before we recommend a single new purchase, we find out what you own and turn it on. Frequently that alone closes most of the gap.

Microsoft 365
Power Automate

Included with most business plans. Sitting unused at the majority of companies we assess.

Already licensed
Microsoft 365
SharePoint & Lists

A capable structured data layer that most organizations use as a file folder.

Already licensed
Power Platform
Dataverse & Power Apps

Enterprise-grade data platform sitting inside entitlements nobody opened.

Often included
Microsoft
Excel & Power Query

The transformation engine inside Excel that most teams have never been shown.

You've owned it for years
Google Workspace
Apps Script

A full automation runtime attached to every Workspace account. Almost nobody uses it.

Free with your account
Google
Looker Studio

A genuinely capable BI and dashboarding layer that costs nothing to use.

Free
Google Cloud
BigQuery

Serverless warehousing with a free monthly tier most small companies never exceed.

Free tier, then pennies
Google Workspace
Sheets & Connected Sheets

Query billions of BigQuery rows from a spreadsheet interface your team already knows.

Already licensed

How we work

We sell the solution, not our hours.

Most consultancies are structurally motivated to stay. Every hour they bill is revenue, so the work is never quite finished and the documentation is never quite complete. We run the opposite model: fixed price, defined end, and a deliberate handoff to your own people.

WE BUILD

Designed and delivered

The automation, dashboard, warehouse, or integration — built to spec, tested against your real data, and running in your environment, on your tenant, under your accounts.

WE DOCUMENT

Written down properly

A real runbook: how it works, what it touches, what to do when it breaks, and how to change it. Not a slide deck. The kind of document that still makes sense to someone who joins your company two years from now.

WE TRAIN

Super users, on your staff

We train people already on your payroll to own and operate what we built. They become the internal experts. No new headcount, no permanent dependency on an outside firm.

WE LEAVE

And that's it

You own the files, the code, the queries, the credentials, and the documentation outright. If you never call us again, everything keeps running. That is the deliverable.

Ongoing support is available, never required. Some clients want a monthly block for changes and new reports. Others take the handoff and run it themselves for years. Both are fine — and we would rather you choose the second one than be quietly sold the first.

The obvious question

Why use a consulting firm instead of just hiring someone?

It's the right question, and for a handful of companies the honest answer is that you should hire. For most, the arithmetic doesn't support it — and the reasons are the same ones that make this an easy approval upstairs.

The work is finite. A salary is not.

Most companies have six to twelve months of real data work — not a career's worth. Once the builds are done, what remains is maintenance measured in hours per month. Hiring for a finite project creates a permanent cost center, and the hardest expense to remove from a budget is one with a person attached to it.

A project is far easier to get approved than a headcount.

A fixed-price engagement is a single line item that often sits inside a director's or VP's existing signing authority. A new requisition goes through finance, HR, and a hiring committee, and can take two quarters to clear. Same money, a fraction of the friction — and no permanent addition to the org chart to defend next budget cycle.

Loaded cost is roughly 1.3× the salary.

Payroll taxes, health coverage, retirement match, PTO, equipment, software licenses, training budget, unemployment insurance. A $90,000 analyst costs closer to $120,000 — and if you use a recruiter, add 15–25% of first-year salary on top before they've done a day's work.

Three to five months before a hire produces anything.

Writing the req, posting, screening, interviewing, an offer cycle, a notice period, onboarding, and ramp-up. That's a full quarter or two of paying for the problem you were trying to solve. We deliver in two to six weeks, with a working demo at the halfway mark.

One hire gives you one skill set. This gives you the whole stack.

Automation, business intelligence, data architecture, EDI integration, performance tuning, and process engineering — across both the Microsoft and Google ecosystems. Very few individual candidates at that salary have all of it, and the ones who do are expensive, in demand, and recruited away within eighteen months.

End-to-end means you don't staff the rest of it either.

Discovery, requirements, architecture, build, testing, documentation, training, and handoff — all of it. No separate business analyst, project manager, technical writer, or trainer to hire or borrow. One engagement, one price, one person accountable for the outcome.

Fixed price moves the risk off your side of the table.

If the build takes 40% longer than estimated, that is our problem and the invoice doesn't move. A hire who underperforms is your problem for six months, followed by a difficult conversation, a severance question, and starting the search over.

Key-person risk disappears instead of concentrating.

The usual failure mode: one person builds everything, understands everything, and then leaves — taking the system with them. We document to a written runbook and deliberately train more than one person on your staff, precisely so that can't happen. That's a deliverable, not a nice-to-have.

You keep the capability without keeping the cost.

After handoff, your own trained super users own and operate what we built. You gain an internal expert without adding a salary — the knowledge transfers, the payroll obligation doesn't.

Scale it up or stop it cold.

Need more next quarter? Scope another project. Need nothing? Then you pay nothing. There is no notice period, no severance, and no awkward restructuring — the relationship ends cleanly the moment the work does.

Making the case internally

"This isn't IT spend. It's a labor cost we're removing, with a payback period we can put on one slide."

  • The recurring cost we're eliminating — from the calculator, in your own numbers.
  • The one-time cost to eliminate it — fixed, capped, approved in advance.
  • The payback period — usually weeks, not years.
  • What happens after — nothing. No renewal, no license, no headcount.

Export the calculator as a PDF, slide deck, or spreadsheet with all four filled in.

And if you actually should hire — we'll tell you. If your data work is genuinely full-time and ongoing, a permanent analyst is the right answer and we'd rather say so in the free hour than take a project we don't believe in. We'll even help you scope the role, and build the foundation that person inherits on day one instead of spending their first six months constructing it.

What it costs

The three ways to solve this, priced honestly.

There are really only three options once you decide the problem is worth fixing. Here is what each actually costs.

  Hire it in-houseBI analyst, full-time National consultancyBilled hourly KADxFixed-price build
First-year cost $95,000 – $125,000
Salary plus payroll tax, benefits, equipment, and PTO
$175 – $300 / hour
A comparable scope typically lands between $30,000 and $60,000
$4,500 – $15,000
One number, agreed before work starts
Time to first result 3–5 months — recruiting, hiring, onboarding, ramp 6–12 weeks, after a discovery phase you also pay for 2–6 weeks, with a working demo at the halfway mark
What happens after A permanent salary line, whether or not there's a permanent workload A support contract. The documentation tends to stay thin. Nothing. You own it, your staff runs it, the cost stops.
Who ends up owning it One person — and it leaves when they do The firm. That is generally the business model. Your team. Trained deliberately, as a deliverable.
Risk if it goes wrong A hire you have to manage out An open-ended invoice A capped, fixed number you approved in advance
On-site in southern Arizona Yes, once hired Rarely — and travel is billed Yes. Based in Tucson, no travel charges.

In-house figures reflect typical loaded cost for a mid-level BI analyst in southern Arizona. Consultancy rates reflect published market ranges for comparable firms. Verify both against your own quotes — we would rather you check than take our word for it.

Track record

The numbers behind the pitch.

Systems Kyle Reep designed and built at The Wonderful Company (FIJI Water and JUSTIN Vineyards) and Maximus (federal and state healthcare contracts). The figures are measured, not rounded up.

16 hrs → 15 min

A month-end document audit and traceability cycle, rebuilt as an automated Python routine.

Automation · Wonderful Co.
50% faster

Refresh latency cut on a 1.6M-row model through query folding and complexity optimization — sub-second response for global executives.

Performance engineering · Wonderful Co.
+48%

Logistics scheduling efficiency after end-to-end RPA pipelines eliminated manual data entry bottlenecks.

RPA · Wonderful Co.
−65%

Time spent searching for internal information, after custom AI agents were deployed against existing documentation.

Agentic AI · Wonderful Co.
1.6M+ rows

Legacy SharePoint reporting migrated into a centralized Snowflake and Dataverse architecture supporting a multi-brand portfolio.

Data architecture · Wonderful Co.
−32%

Executive reporting review time, after manual aggregation was replaced with automated status generation.

Reporting automation · Maximus
+16.8%

Program-wide data throughput following SQL-based root cause analysis on system anomalies and data silos.

Root cause analysis · Maximus
100% adoption

On executive dashboards built for non-technical stakeholders — with zero training required.

Design

Who you'll work with

Kyle Reep, Founder & Principal

The person in your free assessment is the person who builds it. No hand-off to a junior team, no account manager in between.

I've spent years building data systems inside large organizations, from consumer brands like FIJI Water and JUSTIN Vineyards at The Wonderful Company to federal and state healthcare programs at Maximus. The work always had the same shape: find where people are doing work software should be doing, then build the system that ends it.

KADx brings that same enterprise-grade work to companies that don't have a data team of their own.

  • EducationGraduate-level Computer Science
  • CertifiedSoftware Development, AI Development, Data Analytics, Teaching, and Lean Six Sigma
  • PlatformsMicrosoft 365 & Power Platform · Google Workspace & Cloud · Snowflake · SQL Server & BigQuery · Power BI, Looker Studio & Tableau
  • Build toolsPython · SQL · JavaScript · Java · VBA · REST APIs · UiPath RPA · Copilot Studio & LLM agents · EDI
  • BasedTucson, Arizona

Engagement

No discovery phase that bills for four months.

STEP 01

Free assessment

Sixty minutes, on-site or remote. You walk us through where the hours go. We tell you what's worth automating and what isn't. No charge, no obligation.

STEP 02

Fixed-price scope

Within three business days: a written proposal stating exactly what gets built, what it costs, and when it's done. One number. No hourly surprises.

STEP 03

Build & demo

Two to six weeks depending on scope, with a working demo at the halfway mark so nothing is a surprise at the end.

STEP 04

Document, train, hand off

Runbook written, super users trained, credentials and files transferred. You own everything. We're done.

Pricing

Published up front, deliberately below market.

You should know roughly what this costs before you call anyone. The final number comes out of the assessment; these are the starting points.

Dashboard Sprint

$4,500 starting
2 weeks
  • One dashboard — Power BI or Looker Studio — on a properly built data model
  • Up to two data sources connected and transformed
  • Automated refresh on your schedule
  • Runbook, handoff, and super-user training
Contact us
Most common

Operations Package

$15,000 starting
4–6 weeks
  • Three to five dashboards across departments
  • Two automated workflows replacing manual processes
  • Consolidated data model, cleanup, and governance rules
  • Full documentation and super-user training
  • 30 days of post-launch support included
Contact us

Automation Build

$7,500 starting
3–4 weeks
  • One high-volume manual process automated end to end
  • Error handling and failure alerting built in
  • EDI mapping and partner onboarding available
  • Runbook, handoff, and super-user training
Contact us

Optional ongoing support: from $1,200/month. Report changes, new dashboards, monitoring, and a standing block of hours. Month to month — no annual contract, and never a condition of the build.

Questions

Straight answers.

How are you this much cheaper than everyone else?

Low overhead and a deliberate choice about who we serve. We have no downtown office, no sales team, no layer of account managers, and no partner margin to feed. We also don't bill for a discovery phase — the assessment is free because it takes an hour, not a month. The work is the same work; you're simply not paying for the building it usually gets done in.

What does "we sell the solution, not our labor" actually mean?

It means the engagement has a defined end, and reaching it is our job rather than a revenue problem. We build it, document it properly, train people on your payroll to run it, and hand over every file and credential. If you never speak to us again, nothing stops working. Ongoing support exists if you want it, but it is never a requirement and never a dependency we engineer in.

We're a small company. Is this overkill for us?

Usually the opposite. Large companies have a data team absorbing this work; small companies have one overloaded person doing it after hours. Run the calculator above — if anyone at your company spends more than a day a month on a repetitive task, the arithmetic already works, and it works harder the smaller you are.

We run on Google Workspace, not Microsoft. Is that a problem?

Not at all — we work in both ecosystems and have no preference. On the Google side that means Looker Studio for dashboards, BigQuery for warehousing, Apps Script for automation, and Connected Sheets so your team can query millions of rows from an interface they already know. We fit the stack you own. If you're running a mix of both, that's extremely common and we'll help you decide what belongs where.

Do we need to buy new software?

Usually not. Most of what we build runs on licensing you already hold. On Microsoft that's Power Automate, SharePoint, Excel's Power Query engine, and often Power BI. On Google, Apps Script comes with every account, Looker Studio is free outright, and BigQuery has a free monthly tier most small companies never exceed. The first thing we do is find out what you own. If something genuinely needs buying we'll say so and tell you what it costs — we don't earn anything on your licenses either way.

Our data is a disaster. Do we need to clean it up first?

No. Cleaning it up is part of the job, and "our data is a mess" is what almost everyone says on the first call. Send it as it is.

What if the process we want automated shouldn't be?

We'll tell you. Automating a broken process just produces broken output faster, and some tasks genuinely aren't worth the build. Getting told "don't pay us for that" in the free hour is a legitimate outcome of the assessment.

Who owns what you build?

You do — outright, in writing. The files, the code, the queries, the automations, the documentation, and every credential. It runs in your environment on your tenant from day one.

Do you work on-site or remotely?

Both. We're based in Tucson, so on-site anywhere in southern Arizona is straightforward — and we'd rather watch the actual process than hear it described. Build work happens remotely, and we work with clients nationwide.

Get started

Tell us where the hours go.

Sixty minutes, no charge, no pitch deck. Worst case you get a free expert opinion on what's worth fixing and what isn't.

Email hello@kadxconsulting.comWe reply within one business day.
Service area Southern ArizonaTucson, Nogales, Rio Rico, Sierra Vista, Marana, Oro Valley, Green Valley — and remote engagements nationwide.
Response Assessments within the weekMost builds start one to two weeks after a signed proposal.

Goes straight to our inbox. We reply within one business day.