DRYVN COMMERCE · LIVE ACROSS PARTS, MARINE & OFF-ROAD CATALOGS

Every SKU. Every channel. Proven daily.

DRYVN Commerce pulls your catalog from wherever truth lives — store, distributor file, supplier API — and publishes one validated version to Google, Microsoft, Meta, and TikTok. Bad data gets refused. Every sync gets audited. And the receipts post to your Slack every morning. It's the job enterprise feed platforms charge four figures a month for — plus the intelligence layer they don't have.

Get connected$997/mo · live in 2 business days

The problem, stated plainly

Five sources. Zero agreement.

An online store's product data lives in five places and agrees in none of them. The supplier's feed says one thing, the storefront another, Google Merchant Center a third. Products get disapproved and nobody notices for weeks. A promo price leaks to an ad channel after the sale ends. Customers search for what you sell, get zero results, and leave. None of this shows up on a dashboard as a single red light — it shows up as revenue that quietly doesn't happen.

What the system does

It moves product data the way it should move.

It ingests from wherever the truth lives — the store, a distributor's file drop, a supplier's API — normalizes everything into one canonical catalog, and publishes it to the channels that sell: Google, Microsoft, Meta, TikTok. Prices, promo windows, identifiers, category attributes, compliance flags — carried correctly, kept current.

Then it does the part feed tools can't.

Because it runs on the same data foundation as the rest of my operating system, it sees how buyers actually behave — what they search for and don't find, where navigation dead-ends, which channel disapprovals trace back to which catalog gaps. Every week it turns that into specific, evidenced recommendations: fix this category mapping, restructure that collection, add these search synonyms. Safe mechanical fixes it applies itself — behind an approval gate. Structural changes get a plan, not a silent edit.

Running in production

Not a roadmap. Yesterday's sync logs.

DRYVN Commerce runs today across performance-parts, marine, and off-road catalogs. These numbers are from live operations, not a pitch deck.

29,032

inventory positions

synced 4× a day on one catalog. Hash-checked — unchanged feeds skip in seconds.

10,054 + 26,715

created + updated

in a single distributor sync. Zero failures. Every run audited.

4,234

SKUs per channel, daily

to Google Merchant and Meta Catalog — promotions synced, availability inline.

100%

of runs audited

pass/fail to a sync table, posted to Slack. No vibes, receipts.

55,492 → 29,032

rows pre-filtered

orphaned updates eliminated before they ever touch the store.

2 days

purchase to connected

onboarded by the team that runs it — not handed a dashboard.

Your ops room is a Slack channel, not a portal.

Every deployment gets its own commerce channel. Syncs post their results as they run, the Daily Commerce Feed digest lands every morning, and Order Intelligence raises anomalies the moment they're detected — unshipped orders, return spikes, velocity mismatches.

These are the actual message formats the system posts. When something needs a decision, it's raised as a question in the channel — not buried in a log you'll never read.

# your-brand-commerce

DRYVN FeedAPP8:30 AM

📅 Daily Commerce Feed — Aug 11, 2026

Product Sync

Runs: 3 — ✅ 3 success

Google Merchant 4,234 · Meta Catalog 4,234 · Google Promotions 3 · 4 skipped (ineligible)

Inventory Sync

Runs: 1 — ✅ 1 success

Totals: 6,420 variant levels current · 0 failed · availability sent inline on every push

✅ 1

DRYVN FeedAPP2:14 PM

⚠️ Order Intelligence

3orders unshipped >48h · velocity mismatch on RTT-044 (14 sold/7d, 2 on hand) — reorder or cap the channel?

The deep end

Built for catalogs that fight back.

Supplier and distributor ingest, done properly.
Turn14-class supplier APIs, ACES/PIES industry feeds, distributor file drops — pulled on schedule, normalized into the canonical catalog, and reconciled against the store instead of blindly overwriting it.
Fitment intelligence for parts catalogs.
Vehicle-fitment data crosswalked against the SEMA VCdb standard with similarity-scored matching — so year/make/model accuracy holds at catalog scale, and fitment rides into the store as structured metafields, not a PDF nobody reads.
Write-back to the store as source of truth.
Categories, GTIN/MPN identifiers, custom labels, fitment metafields — enriched centrally, written back to Shopify, so every downstream channel inherits the same clean record.
Validation before publish, always.
Every feed change passes validation before a channel sees it. Bad data gets refused, not shipped. Per-channel eligibility is tracked per SKU, so you know exactly what's live where — and why anything isn't.

How it's built

The method is the proof.

One catalog, source-stamped.
Every field knows where it came from and how much to trust it. A distributor feed can fill a gap; it can never overwrite what a human curated. Safety warnings can be added by any source and removed by none.
Guarded writes, provable dry-runs.
Nothing pushes to a live ad channel without passing a target allowlist that’s enforced three separate times. Dry-run mode provably makes zero external calls. Every sync is designed to be auditable after the fact.
Refuses bad data on its own.
When an inbound feed shrinks or mutates beyond safe thresholds, the system halts the sync instead of propagating the damage — then tells a human. This isn’t hypothetical: it recently caught a corrupted supplier file that would have silently erased most of a store’s catalog from its ad channels. The gate held, twice, until the supplier fixed their export. That’s the difference between a feed tool and an operating system.
Recommend first, write second.
The intelligence layer earns trust by showing its evidence in a weekly packet before it ever touches anything. Human judgment stays in the loop where it belongs.

Built with an AI team

Specified, vetted, and built by AI — deliberately.

This system was specified, reviewed, and largely built by AI — deliberately, and with the gates showing. The product spec was drafted by an AI thinking partner, then adversarially vetted by three AI specialists: a catalog domain expert who caught a compliance-handling gap, an engineer who verified the code and corrected a platform-rules assumption against live documentation, and a strategist who pressure-tested the commercial framing with verified market data. Every finding was incorporated before a line of new code was planned. The build itself runs on an AI fleet with human approval gates at every consequential step.

That's the actual thesis of this site: AI doesn't replace operating judgment — it makes judgment enforceable at scale. A system like this is what that looks like when it's real.

Where it fits

DRYVN Commerce is one system inside DRYVN — the operating discipline I run businesses against. The catalog it maintains is the same catalog the AI co-worker reads, the weekly proof packet reports on, and the ad channels sell from. One source of truth, consumed everywhere.

Pricing

One base. Two modules. No surprises.

The system

DRYVN Commerce

$997/moup to 50K SKUs · up to 4 channels

Google, Microsoft, Meta, TikTok publishing
Canonical catalog + Shopify write-back
Validation gates on every change
Audited syncs + daily Slack digest
Weekly merchandising recommendations

Module

Supplier Feed Ingest

$297/moper feed

Live catalog, inventory, and pricing pulled from Turn14-class supplier APIs and ACES/PIES feeds — replacing manual exports for good.

Module

Order Intelligence

$197/mo

Unshipped-order alerts, return-trend anomalies, and inventory velocity mismatches — surfaced in Slack before they become revenue problems.

Wondering what your product data is costing you?

Buy today, connected within 2 business days — and onboarded by the team that runs it, not handed a dashboard.

Talk to Brian