| Item | Description | Impact |
|---|---|---|
| Grouped Fulfilments | Consolidated orders into grouped shipments across the network. 35,662 shipments down to 11,216 grouped fulfilments, reducing booking fees and parcel volume. | 68% fewer shipments. Around $392,100 saved in booking fees and freight. |
| Pedal Group App | Built and shipped a custom store app, demoed and launched at the TL Conference. Three modules live (Scan to Receive, Bike Build, Scan to Print), with P&A receiving, stocktake and offline POS on the roadmap. | One platform for store operations. Hours given back to stores. |
| Scan-to-Receive | Scan-to-receive bike receiving. Smart QR labels from Infor WMS into a custom NetSuite receiving interface on a Zebra handheld fleet. Stores receive what is in front of them, no line-by-line matching. | 5,524+ units received by scan. Manual PO matching removed. |
| Split Receiving | Staged, multi-part receiving so stores receive the bikes physically in the store, rather than waiting on the full order. | Fewer stock cases. Faster receiving, cleaner stock. |
| Cario Integration | Delivered the Cario carrier integration replacing Cubiic. Celigo consignment-status sync to NetSuite Track & Trace with a status-regression guard, label SQL improvements, and a ZPL print service. | More warehouse flexibility at around half the cost. |
| Freight Validation AI (FRED) | A learning freight-audit engine (NetSuite + Celigo + Claude + Supabase) that reads plain-English vendor freight terms for DCs and stores, validates every charge, learns from each review, and auto-approves under a $5 tolerance. | 32,566 bills audited. $52,106 in discrepancies caught. AI-VALIDATED$0.00 net, FY26 |
Bonjour, and welcome. I'm a quick way to review Mikah Villeprat's FY26 contribution as Operational Platforms Leader in Technology.
Ask me anything, or tap a topic below. Full disclosure: I'm a curated stand-in, not a live model. Mikah built the real AI this year. I'm just the front desk, with a bit of cheek.
Plenty. The headline six:
Want the numbers, or the AI detail?
The FY26 scoreboard:
The grouping took 35,662 shipments down to 11,216 grouped fulfilments and saved around $392,100 in booking fees and freight. FRED, the freight-validation AI, audited 32,566 bills and caught $52,106 in discrepancies. Residual after validation: $0.00. Tap Show me the receipt for the itemised version.
The fun part, given what you're using right now.
Mikah designed and shipped FRED, a freight-validation engine: NetSuite, Celigo, Claude and Supabase working together. It reads suppliers' freight terms written in plain English, for DCs and stores, checks every charge against them, and learns from each human correction. This year it audited 32,566 bills and caught $52,106 in freight discrepancies.
He also stood up an autonomous agent layer to take routine technology work off the team. So yes, the irony is deliberate. He built real, working AI this year, and his submission is a fake one.
I didn't write these. They're real MVP nominations from across the business, picked up stage by stage through FY26:
A handful of the nominations, kept short. There were more across the year.
Because it ladders straight to the purpose: to enrich the mind, body, earth or soul through the freedom of riding.
Every project here gets bikes to riders faster and with fewer mistakes. Cleaner receiving across 80+ stores. Far fewer shipments, which means less freight, less packaging and less waste, around $392,100 saved. Suppliers billed correctly, automatically. It's quiet plumbing, but it's the plumbing the whole retail and wholesale operation runs on.
Non. I'm a curated stand-in, hand-written by Mikah.
The real AI he shipped this year, FRED, audits every supplier freight charge automatically and learns as it goes. Think of me as a demo with a sense of humour. For the substance, tap What did Mikah ship in FY26? or Show me the receipt.
Here's the itemised version. Opening the Statement of Value now. Use Save as PDF inside to download it.
Good question, though I only know Mikah's FY26 story, I'm afraid. Try a topic below, or ask about his projects, the numbers, the AI work, or what his colleagues say.