Currently Accepting 1 New Client · Q2 Power BI · Data Infrastructure

When a client says your report is wrong, do you know why?

That email, call, or meeting where the numbers don't align — it's more than a technical problem. It's a trust problem. While you're trying to determine who's right, your client is quietly reconsidering how much they believe you.

Book a Free Discovery Call → 30 minutes · No pitch · No obligation
23YRS
In high-consequence
data environments
$360K+
Single-client contract
saved from a failure
F500
Clients served via
platforms built from scratch
1:1
Engagement model
Senior attention only
Power BI Architecture Data Warehouse Design ETL & Pipeline Engineering Client-Facing Reporting Regulatory Data Compliance Source System Integration Validation & QA Layers Embedded Analytics Power BI Architecture Data Warehouse Design ETL & Pipeline Engineering Client-Facing Reporting Regulatory Data Compliance Source System Integration Validation & QA Layers Embedded Analytics
01 The Diagnosis

A discrepancy surfaced. The question is where it came from.

Data errors are rarely where they appear. By the time a client flags a number, the root cause has usually been sitting quietly in your system for weeks. Finding it means moving through the entire stack — from source to transformation to display — with someone who has done it enough times to know where to look first.

01 / Data Ingestion

Upstream sources don't announce when they've changed.

Vendor systems update without notice. File formats drift. Data arrives differently than your system expects. These failures are silent — they sit in the pipeline until a client catches what your monitoring missed.

02 / Logic Layer

Calculations that worked in testing can break in production.

Logic that passes QA under controlled conditions can fail under real-world combinations of filters, date ranges, and edge cases. The discrepancy you're seeing today has usually existed longer than anyone realized.

03 / Architecture

Decisions made years ago are governing you today.

Whether reporting stays accurate as volume, complexity, and client requirements grow is determined by choices made in the original build. Structural problems don't announce themselves early — they compound.

02 Who I Help

Built for companies where wrong data has real consequences.

My work centers on one principle: reporting you show to clients, regulators, or your own leadership cannot afford to be quietly wrong. I lead with a flagship vertical where that principle is non-negotiable, and extend the same discipline to growing companies in adjacent industries.

Flagship Vertical

International Trade & Customs Operations

Where I've spent two decades. In customs, wrong data has consequences beyond a client complaint — regulatory exposure, goods held at the border, financial penalties, and fractured relationships that took years to build.

  • U.S. & Canadian Customs Tracking
  • ISF · Commercial Invoice · Financial Detail
  • Power BI Embedded Client Portals
  • Source-to-Report Validation Layers

Growing SMBs where the same discipline applies

If your company is past the spreadsheets-and-hope stage and your reporting now influences revenue, compliance, or client trust — you're in the territory this work is built for.

  • / 01
    Logistics & Supply Chain Freight forwarders, 3PLs, carriers with client-facing reporting SLAs.
    →
  • / 02
    Regulated B2B Services Firms reporting to clients where audit trails and data lineage matter.
    →
  • / 03
    Financial Operations Companies with multi-source reconciliation and client-facing dashboards.
    →
  • / 04
    Professional Services at Scale Agencies, consultancies, firms billing complex work against reported metrics.
    →

Context

A Fortune 500 importer raised an issue with their customs brokerage: the reports they were receiving didn't match their internal records. The discrepancy had been building for weeks. Their contract was up for renewal in 30 days.

Diagnosis

The system appeared to be running normally. But the failure was in a processing layer pulled from a vendor's upstream system — the kind of silent break that leaves no error logs and doesn't trip any monitoring. Wrong numbers had been reaching client-facing reports cleanly.

The system was technically working. Every dashboard was green. The numbers were wrong anyway.

The Build

I built a Power BI validation layer to cross-check the vendor's calculations against source-of-truth data, identified the full set of errors, rewrote the affected logic, and added automated validation so similar failures would surface internally before reaching any client-facing report. Then I audited the rest of the pipeline for the same exposure.

Outcome

The client started receiving accurate reports the same week. The contract was signed for a multi-year renewal. The brokerage now runs with a monitoring layer that surfaces data issues internally — before any client ever sees them.

04 How I Work

Three stages. Each one fully defined before it begins.

No questionnaires. No proposal calls that waste everyone's time. Every engagement follows the same structure, so you always know exactly what you're getting and what it costs before we move forward.

Stage One 01 / 03

Discovery Conversation

A real conversation about your situation, your data environment, what your reporting needs to do, and where it's currently failing. We'll both know by the end whether it makes sense to continue.

Free · 30 Minutes
Stage Two 02 / 03

Structured Assessment

A written assessment of your complete reporting environment — sources, processing, architecture, output. Specific findings, root causes, and a prioritized plan. Yours regardless of what comes next.

Stage Three 03 / 03

Implementation

Whether fixing, rebuilding, or building from scratch — scope, timeline, and deliverables are defined before work starts. I work with a small number of clients at a time so every engagement gets senior attention.

Fixed Scope · 3 Weeks – 3 Months
ID / 001 INFINEXT · FOUNDER
Replace with real headshot 4:5 recommended
05 About

23 years inside the data international trade runs on.

I built the first client-facing data portal for a Top 20 U.S. customs broker in 2003. Over the following two decades, I expanded it into the complete reporting infrastructure their Fortune 500 clients relied on — because those clients couldn't afford for it to be wrong.

The platform grew to cover U.S. and Canadian Customs tracking, commercial invoice and ISF filing, financial detail reporting, document access, custom report generation, and most recently a full Power BI Embedded implementation. I built the data infrastructure and the validation logic that kept it accurate when source systems updated, regulations shifted, or a vendor changed something without notice.

In Customs, wrong data has consequences beyond a client complaint: regulatory exposure, goods held at the border, financial penalties, and fractured relationships that took years to build. That environment is where I worked for over two decades. The discipline it required is what I now bring to growing companies where the same stakes apply.

LinkedIn ↗ Full CV ↗ References on request
06 Common Questions

Questions I hear before the first call.

Most of what's asked on a discovery call is a variant of the six below. Answers here so you can skip ahead.

Most Power BI consultants work from the reporting layer down. They build dashboards on top of whatever data you've got.

My background is building and maintaining complete data infrastructures — source systems through processing, warehousing, and reporting — in environments where errors carry compliance and client-relationship consequences. The reporting layer is the last mile; the real work is everything underneath. That's a different scope of engagement.

Most companies have underlying data problems that prevent them from relying on their reports for critical decisions. These show up as symptoms — missing data, numbers that don't look right, report refreshes that fail.

A real assessment means moving through your actual systems, not reading a brochure. It takes real work. Charging for it ensures you receive something of genuine value — a written document you keep, regardless of whether you choose to work with me on implementation — and filters for clients serious about solving the problem.

A free 30-minute conversation first. If there's a fit, a paid, scoped assessment. If you want to move forward after that, a clearly scoped implementation engagement. Every stage is fully defined in writing before it begins — no surprise scope, no open meters.

I work with a small number of clients at any one time. You'll work with me directly, not a junior handed the project after the sale.

Typical engagements run from 3 weeks to 3 months, depending on the number of source systems, the complexity of existing integrations, and the current quality of the underlying data.

The exact timeline is defined in writing before we start — not estimated and adjusted as we go.

Assessments typically range from $4,000 to $12,000 depending on the number of systems and the complexity of your reporting environment. Implementations are scoped to the work and quoted as fixed-price engagements — never hourly, never open-ended.

If budget fit is unclear, the discovery call is the right place to find out. It costs nothing and takes 30 minutes.

Yes, if the core problem is the same: reporting your business or your clients rely on, where accuracy is non-negotiable, built on data from multiple sources that have to stay aligned.

The discipline transfers. The most common question on the discovery call is whether your situation fits — and most of the time, if you're reading this page, it does.

07 Next Step

Get reporting your clients never question.

True confidence in your reporting means clients who renew without friction, refer without being asked, and never need to pick up the phone to challenge a number. The next step is a 30-minute conversation.

Book a Free Discovery Call → 30 minutes. No pitch. No obligation. You'll leave with a clearer sense of the problem regardless of whether we work together.