Taking two projects for September 2026

Repetitive workis a bug.I write the fix.

I design and build automation systems for companies that are done doing things by hand — integrations, internal tools, AI agents, and pipelines that run all night so your team doesn't have to.

Book a callSee the work
overnight · production loglive

02:14:07 ✓ 847 orders synced → ERP

02:31:52 ✓ invoice batch posted · 0 exceptions

03:02:19 ✓ 1,204 leads enriched · 38 duplicates dropped

03:40:44 ✓ inventory reconciled across 3 warehouses

04:15:08 ✓ 92 support tickets resolved · 4 escalated

0
systems in production
0k+
hours of manual work eliminated
0.00%
uptime across everything I run
0
systems abandoned by clients

01Selected work

Systems that replaced entire job descriptions.

01Eight-figure ecommerce brand

Shopify ↔ ERP, reconciled to the cent

The problem

Every order, refund, and inventory change was retyped into the ERP by hand. Fourteen hours of data entry a day, and a 4.1% error rate that finance discovered at month-end.

The build

An event-driven sync layer between Shopify and the ERP: webhook ingestion, an idempotent job queue, two-way conflict resolution, and a reconciliation report that flags anything the system refuses to guess about.

TypeScript · Temporal · Postgres · Shopify Admin API

14h → 0
daily manual entry
0.02%
error rate, from 4.1%
11 days
to first production sync

02B2B lead-generation agency

A lead-enrichment engine that never sleeps

The problem

Six researchers copy-pasting between LinkedIn, company sites, and spreadsheets produced roughly 400 enriched leads a week — with stale data and duplicated effort across clients.

The build

A scraping and enrichment pipeline: source discovery, headless-browser collection with rotating sessions, entity resolution across sources, and scoring tuned per client. Fresh, deduplicated leads land in the CRM every morning.

Python · Playwright · Postgres · Clay API

12,000+
leads enriched monthly
2.1% → 7.4%
cold-email reply rate
6 → 1
researchers on data entry

03DTC brand, 40k tickets/year

Support that resolves itself

The problem

Support spent most of its day on the same five questions — order status, returns, address changes — while genuinely hard tickets waited hours in the same queue.

The build

An AI triage layer in front of the helpdesk. It reads every ticket, pulls order context from Shopify and the 3PL, resolves the routine ones end-to-end, and hands the rest to a human with a written summary and suggested action.

Claude API · Node.js · Zendesk · Shopify

68%
resolved with no human touch
4.8 / 5
CSAT — unchanged
9 min
median resolution, was 6 hrs

04Logistics company, 120 staff

Month-end close in 36 hours, not nine days

The problem

Finance closed the books by exporting CSVs from four systems, stitching them together in Excel, and chasing discrepancies over email. Nine days, every month, for years.

The build

A finance pipeline that pulls from all four systems nightly, normalizes and matches transactions, posts journal entries automatically, and produces an exception list — so the team investigates differences instead of hunting for them.

Python · dbt · Airflow · NetSuite API

9 d → 36 h
month-end close
~2,300 h
saved per year
100%
transactions traceable

02What I automate

If your team does it twice a week, it's a candidate.

03Process

No discovery phases that discover nothing.

  1. Week 0

    Diagnose

    A short call, then I trace the workflow end to end — who touches what, where time actually goes. You get a written map of the system and a fixed quote. If automation isn't worth it, I'll say so.

  2. Week 1

    Prototype

    The first deliverable is working software, not a deck. Within days, a thin version of the system runs against your real data so we find the awkward edge cases early — there are always edge cases.

  3. Weeks 2–6

    Ship

    The full system, hardened: retries, alerts on failure, an audit trail, and documentation your team can actually read. It runs in your infrastructure, under your accounts. You own all of it.

  4. Ongoing

    Run

    Automation earns trust by being boring. I monitor every system I ship, fix anything that breaks, and check in as your volume grows. Most of what I build runs for years without a rewrite.

04Why companies hire me

Not for the easy stuff. For the problem three other people quoted, then quietly stopped replying about.

Legacy ERPs with no documentation. Sites that fight scrapers. Five systems that each believe they own the truth. That's the work I take — and how I work is simple:

Working software over slideware
You'll see the system running against real data before you've finished your first invoice. Proposals are one page; the prototype is the pitch.
You own everything
Code, infrastructure, credentials, documentation — all in your accounts from day one. Firing me should be easy. That's the point.
Fixed scope, fixed price
I quote the outcome, not the hours. If it takes me longer, that's my problem — you knew the number before we started.
Built to be boring
The best automation is the kind you forget exists. Retries, alerts, audit trails, and a plan for every failure mode I could think of — plus the ones production taught me.

05FAQ

The questions every founder asks.

Most systems land between $8k and $40k, fixed price, quoted after the diagnosis. The honest benchmark: if the workflow doesn't waste at least that much per year in salary or errors, I'll tell you not to hire me.

06Contact

Stop doing it by hand.

Thirty minutes. Bring the workflow that eats your team's week — I'll tell you what I'd build, what it costs, and whether it's worth automating at all.

Book a callwarsnoop@apptics.ai

Taking two projects for September 2026