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§ Selected Work / 2024–2026

Quiet systems,
loud results.

Six engagements, told the way the operators on the ground would tell them: what was painful, what we changed, and what the business noticed afterwards. If one of these sounds like your week, it probably is.

001 / 006BI · PipelinesNORTHWIND LOGISTICS
Regional freight & 3PL · ~$120M revenue

One morning dashboard instead of seven spreadsheets.

Before

Every morning at 6 a.m., two ops analysts pulled exports from the TMS, the WMS, the fuel card portal, two carrier portals, QuickBooks, and a driver-hours spreadsheet — then spent three hours reconciling them by hand before the daily stand-up.

What we built

We connected those seven systems to a single warehouse, agreed on one definition of "on-time" and "load cost," and built a live dashboard the ops director opens on her phone before the meeting starts.

After

Stand-up now starts with a number everyone trusts. Both analysts are back on margin analysis and carrier negotiations — work that actually moves the P&L.

Role
Architecture · BI
Year
2026
Result
7→1Systems unified
SnowflakedbtLookerAirflow
You'll recognize this if…
  • Your team starts the day by copy-pasting between spreadsheets
  • Two managers can quote different revenue numbers for the same week
  • You hire analysts and they spend half their time as report-runners
Read the full case study →
002 / 006AI · WebHELIO FINANCIAL
Specialty commercial lender · ~80 underwriters

An AI assistant that drafts loan memos in your firm's voice.

Before

Every underwriter wrote a 6-page memo per deal, mostly from scratch. New hires took 9 months to write memos partners would sign without rewrites. Senior underwriters were a bottleneck on every approval.

What we built

We fed the assistant a decade of approved memos (with the redlines) so it learned the house style, the deal types you accept, and the red flags your partners actually care about. Underwriters open a deal, the first draft is already written; they edit and submit.

After

A new analyst writes a defensible first draft on day one. Senior underwriters review instead of rewrite. The firm closes more deals without adding headcount.

Role
AI · Product
Year
2026
Result
12×Faster first drafts
AnthropicpgvectorNext.jsModal
You'll recognize this if…
  • Your team writes the same kind of long-form document over and over
  • Quality varies wildly between your senior and junior people
  • Years of institutional knowledge live in PDFs no one reads
Read the full case study →
003 / 006IntegrationsARDENT HEALTH
Multi-site outpatient group · post-acquisition

Two acquired companies, one patient record — without changing how clinicians work.

Before

After the acquisition, both groups kept their old patient systems. Front desks re-entered patient details twice. Doctors checked two charts. A scheduling change in one system silently broke the other. Leadership wanted to consolidate but couldn't risk a "go-live" outage on day one.

What we built

We put a quiet bridge between the two systems. A change made in either one shows up in the other within seconds — including the audit trail. Staff kept using the system they already knew. We migrated the data underneath, one department at a time, with the ability to roll back any step.

After

No frozen waiting rooms. No re-training. By the time the formal cut-over happened, the new system had already been the source of truth for a month.

Role
Integrations · Infra
Year
2025
Result
99.97%Sync uptime
KafkaDebeziumAWSTerraform
You'll recognize this if…
  • You've acquired (or been acquired) and now run two of everything
  • A "big bang" migration would shut down customer-facing operations
  • Compliance or auditors need to see exactly what changed and when
Read the full case study →
004 / 006AutomationSTRATAFOLD MFG.
Contract manufacturer · 6 plants · $400M revenue

A 40-step purchase order, collapsed to one approval screen.

Before

Buying a $5,000 part took 11 days. The request bounced between email, a SharePoint folder, three signature lines, the ERP, two Excel logs, and a Slack channel. Plant managers were calling buyers at 7 p.m. asking where their parts were.

What we built

We mapped every step, kept the four that genuinely need a human (the approvals), and automated the other thirty-six. Plant managers now see one screen: what they asked for, who has it, when it ships. Auditors get a complete trail, automatically.

After

A typical PO takes under 48 hours. The procurement team stopped being a help desk and started negotiating contracts again. Audit prep that used to take two weeks now takes an afternoon.

Role
Automation · Web
Year
2025
Result
−86%Manual hours
WorkatoNext.jsPostgresVercel
You'll recognize this if…
  • A simple request takes a week because it crosses six tools
  • Your team's job has quietly become "chase the approval"
  • Audit season costs you a quarter of someone's year
Read the full case study →
005 / 006BI · AICLOUDLAYER
B2B SaaS · ~$60M ARR

Seeing next quarter's cloud bill today.

Before

Finance found out about a $180k AWS overage the day the invoice landed. Engineering swore the spike "must have been the new feature." Nobody could prove it before the board call.

What we built

We built a forecast on two years of their own usage data. It now flags abnormal spend the day it starts — not the month it bills — and ties each spike back to the team and feature that caused it.

After

Finance gets a heads-up two months out, with a named owner. Engineering treats cloud spend as a product metric. The next surprise invoice hasn't happened.

Role
BI · ML
Year
2025
Result
94%Forecast accuracy
BigQueryVertex AIdbtMetabase
You'll recognize this if…
  • Your cloud or SaaS bill keeps creeping up and nobody can explain why
  • Finance and engineering argue every quarter about the variance
  • You want a one-line answer when the board asks "is this under control?"
Read the full case study →
006 / 006Pipelines · CloudMERCATOR/
Online marketplace · 8M monthly users

Moving the plumbing while the water stays on.

Before

A senior engineer was losing one week a month babysitting their self-managed data pipeline. Every outage hit the homepage. Hiring more infra people wasn't solving it.

What we built

We migrated the pipeline to a managed service over six weeks, running both side-by-side until we were certain. Customers never saw a change. The on-call rotation shrank from four engineers to two.

After

That engineer is back on product work. The infra bill went down. The team stopped dreading Sunday nights.

Role
Infra · Migration
Year
2024
Result
0sCustomer downtime
ConfluentTerraformDatadogAWS
You'll recognize this if…
  • A core system runs on something only one person fully understands
  • You're paying senior engineers to be janitors
  • A migration sounds necessary but the downtime risk is unacceptable
Read the full case study →

See your business in one of these?
Let's talk.

Tell us where it hurts in plain language. We'll come back within 48 hours with a sketch of where to start — no decks, no jargon.

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