Manufacturer
Factory A
MY · Penang
Cap.78%
Factory B
TH · Bangkok
Cap.92%
Factory C
VN · Ho Chi Minh
Cap.45%
Order context:RD-2026-064 · UK clinic groupFactory A · 300K · 78%Factory B · 200K · QC failed → rework
PLATFORM · PRODUCTION
Run production across factories you don't own — and stop finding out about problems on Friday.
Production management software was built for one shape of operator: a manufacturer producing in their own factory. Trade operators don't fit that mold. You coordinate manufacturing across 2, 5, or 15 external suppliers in three countries. You allocate by capacity and quality, you sample-inspect every lot before release, you live with yield variance, and you find out a lot failed inspection by email on a Friday afternoon.
Production in TradeOS is built for that operator. Allocation across multiple factories. Sampling inspection with photo evidence — AQL for discrete goods, lot-release testing for bulk. QC rework as a formal state in the lifecycle, not an exception in an inbox. Yield tracked against real cost. An AI planner that proposes the optimal split.
Production Board — three factories, twelve lots, ninety days, one operating layer.
WHAT BREAKS WHEN PRODUCTION DOESN'T FIT YOUR BUSINESS
Three production failures the operator finds out about too late.
The batch you can't trace back
A finished batch of generic API fails final assay at the customer's QC. You need to trace which input lots fed which production run, which operator ran which step, which deviation reports were raised — and the audit response is due in 72 hours. Your contract manufacturer's records are in three PDFs and one Excel they keep updated by hand. By the time you assemble the genealogy, the customer has switched to a backup supplier.
The mycotoxin failure at the port
A 22-tonne lot of cocoa arrives in Rotterdam. EU receipt testing flags aflatoxin levels above the limit. The lot quarantines. You scramble to find which supplier batch is in the container, when it was bagged, what other shipments share the same growing lot — and whether the customer's order can be partially fulfilled from a different lot. None of that exists in one place. The cocoa sits in bonded storage at €240/day.
The deviation report nobody read
The contract manufacturer logged a deviation during a specialty chemical batch — temperature exceeded spec for 18 minutes during reaction. The deviation was attached to an email two weeks ago. The batch shipped. The customer's QC finds it three weeks later when the material doesn't perform to spec on their line. You're now mid-recall — and the deviation report has been in your inbox the whole time.
CAPABILITIES
What the Production module does
4.1 · Allocation
Split a production run across factories — by capacity, yield, and price, in one screen.
Demand on one side, capacity on the other. The operator allocates manually or with system suggestions: 300K units to Factory A (best price, 200K free capacity, 96% yield, AQL 1.5 pass rate 94%), 200K to Factory B (slightly higher cost, available, 88% yield, AQL 1.5 pass rate 91%). The system validates each allocation in real time — capacity, pricing, certifications, lead time vs. delivery date. Confirmed allocations create production lots in Planned status, ready for the manufacturer to confirm dates.
Allocation tool · RD-2026-064 · 500K Surgical gloves
Demand1 open
RD-2026-064
UK clinic group
ProductSurgical gloves
DeliveryJul 21 · 90d
IncotermCIF Hamburg
AQL1.5 · L II
Need 500,000 unitsAllocation2 of 3 used
Factory A · MY60%
0300,000500K
✓ capacity✓ pricing✓ certs✓ lead time
Factory B · TH40%
0200,000500K
⚠ capacity tight (92%)✓ pricing✓ certs✓ lead time
CancelCreate 2 lots
Capacity3 mfrs · 90d
Factory A
MY · Penang
Price $0.71Yield 96%AQL pass 94%Lead 38d
Factory B
TH · Bangkok
Price $0.74Yield 88%AQL pass 91%Lead 42d
Factory C
VN · Ho Chi Minh
Price $0.78Yield 93%AQL pass 93%Lead 46d
4.2 · Quality control
AQL sampling with photo evidence — and a rework loop that's a real state, not an email thread.
Every lot moves through QC. The platform calculates the sample size from the lot quantity and the product's AQL standard — for 35,000 units at AQL 1.5, Level II: sample 315 units, accept if defects ≤ 7. The inspector records type, quantity, severity, and photo evidence. Pass advances the lot to Packed; fail triggers a decision task — rework or reject — with the full inspection history preserved on the lot. QC Failed → In Production → QC Pending is a formal lifecycle state, not an inbox.
QC inspection · PL-2026-0142 · Factory B
PL-2026-0142 · 200,000 units Surgical gloves
AQL
1.5 · Level IIISO 2859-1 / ANSI Z1.4
→315 / 200,000SAMPLE SIZE
Accept ≤ 7Reject ≥ 8
Defects found · 6 / 315 inspected
Thickness variance3MAJOR2 photos
Pinhole1CRIT1 photo
Color deviation2MINOR1 photo
Total defects (weighted)8 / 7 threshold · REJECT
PassFail · rejectFail · rework
Corrective action requested
Recalibrate thickness gauges on line 3 before reprocessing the rejected segment. Re-inspect at 100% of original AQL sample size (315 units). Rework lot returns as PL-2026-0142R.
4.3 · Yield
The supplier that promised 96% and delivered 88% just cost you 9% more than they quoted.
A factory that promised 100,000 units and delivered 92,000 didn't just produce 92,000 — they wasted 8,000 units of input you paid for. The platform tracks input vs. output per lot and computes yield. Cost per good unit is the lot's total cost divided by output, not input. Over time the low-yield suppliers reveal themselves. Factory B at 88% effectively costs 9% more than Factory A at 96% despite identical quoted pricing. This shifts how you allocate, which contracts you renew, and where you negotiate hardest.
Yield · Specialty solvent · 6-month rolling
Factory A · INFactory B · CN
% yield · 80–100ManufacturerQuotedYieldPer goodVariance
Factory A IN · 96% yield$4.2096%$4.38baseline
Factory B CN · 88% yield$4.3588%$4.94+$0.56 · 13%
4.4 · AI planner
Compress the monthly planning cycle from a half-day spreadsheet to a five-minute review.
For Business tier and above, an AI planner powered by Claude takes the demand, capacity, pricing, quality scores, lead times, and constraints — and proposes an allocation. "We have three orders due in April totaling 180 tonnes across two cocoa products. Plan production across our three suppliers optimizing for cost." The planner returns a recommendation the operator reviews, adjusts, and confirms. It doesn't execute autonomously.
AI planner · Atlas · 3 orders · April
Operator prompt
We have three orders due in April totaling 180 tonnes across two cocoa products. Plan production across our three suppliers optimizing for cost.
Constraints applied · No more than 50% with any single supplier
· Aflatoxin compliance ≥ 99% lot pass rate
· Lead time ≤ 60 days from confirmation
· Honor Factory A renewal commitment (≥ 80 tonnes)
· Aflatoxin compliance ≥ 99% lot pass rate
· Lead time ≤ 60 days from confirmation
· Honor Factory A renewal commitment (≥ 80 tonnes)
Atlas recommendationclaude · 4.7s
Plan optimizes cost first, then capacity headroom. Total weighted cost $980,000; saves 3.2% versus single-vendor baseline. Factory A leads on cost-per-tonne at 96% yield; Factory C absorbs Cocoa butter to keep Factory B under capacity.
Factory A · CI RD-064, RD-081100 tonnes Cocoa nibsApr 02 – Jun 04CONF 92
Factory B · GH RD-06450 tonnes Cocoa nibsApr 04 – Jun 06CONF 78
Factory C · ID RD-08330 tonnes Cocoa butterApr 09 – Jun 12CONF 88
ApproveAdjustRe-plan
DATA MODEL
A lot inherits its spec, allocates its capacity, and releases its inventory — without anyone retyping anything.
Production sits between Orders and Shipments. Lots inherit specs from Products. Allocations consume capacity in Manufacturers and feed performance scores back. Released goods generate Shipments. QC events update manufacturer scores in Manufacturers › Performance. Nothing copies between sections — Production reads and writes the same records every other section reads and writes.
SectionWhat flowsWhat you see
DEPTH
Where it goes deeper
6.1 · Scenario simulator · Business tier
Find out what a factory shutdown costs you — before the factory shuts down.
What if Factory A's capacity drops 30% in August for the holiday? What if your largest customer doubles their Q3 order? What if Factory B's yield drops to 85%? The simulator is a sandbox — adjust the variable, see impact across the production plan, delivery dates, cost, and fulfillment risk. Save scenarios as named comparisons ( "Factory A holiday," "Demand surge"). Make decisions before the change happens.
Scenario · "Factory A holiday + Factory B yield drop"
Variables
Factory A capacity−30%
Demand (UK clinic Q3)+15%
Factory B yield85%
Baseline · Factory A 100% · Demand baseline · Factory B 88%
Impact
Plan feasibilitytight · 92% confidence
RD-2026-064 delivery+9 days (Jul 30)
RD-2026-081 delivery+2 days
RD-2026-083 deliveryon plan
Total cost delta+$18,400 (+3.1%)
Factory C reroute+140K to Factory C
Lot date shift
PL-0138
PL-0142
PL-0156
6.2 · Predictive QC
Catch the quality slide before the lot that fails ships to your customer.
Quality doesn't usually fail on a Tuesday — it degrades over weeks. The platform tracks QC pass rate per manufacturer × product over rolling 30/60/90-day windows. A pass rate trending from 95% down to 88% over a month surfaces as a yellow flag before a single lot fails. You get a chance to intervene with the supplier — request a third-party inspection, audit the line, ask about staffing — instead of reacting to a failed lot that shipping depends on.
Risk radar · 30-day rolling pass rate
Pass-rate trend by manufacturer × product
Mfr × ProductPharma APITabletCapsuleIntermediateFactory A IN94% +0.496% ±0.095% +0.293% −0.1Factory B CN88% −4.291% +0.192% +0.390% −0.4Factory C VN93% +0.694% +0.294% +0.592% −0.1Detail
A PLANNING CYCLE, END TO END
A day in the life
Carlos manages production for an importer of industrial supplies sourcing from four manufacturers across Vietnam, Malaysia, Thailand, and Türkiye.
It's the first week of the month. The Production › Planning › Demand view shows what needs to be produced over the next 90 days: confirmed orders not yet in production, weighted pipeline deals from sales, reorder triggers from inventory. He clicks into the Allocation tool. The Capacity view shows each manufacturer's available windows; Factory C in Vietnam is at 83% utilization for the next two weeks, the Türkiye factory is wide open after the holiday. He drags 200K units of one product to Türkiye and the system warns: pricing is current but the certification expires in 21 days — confirm with the supplier before the lot starts. He sends a message through the per-lot thread asking for the renewed certificate.
He runs the AI planner on his largest single order — 1.2M units across three SKUs due in 9 weeks. The planner returns a split: 60% Factory A (best yield, slightly higher cost), 40% Factory B (acceptable yield, lower cost, holiday risk noted). He simulates a what-if: Factory B holiday closure adds 4 days. The simulator shows the order still ships on time if Factory A absorbs the rebalance. He approves the original allocation; the lots create automatically.
Mid-month, lot PL-2026-0142 from Factory B fails QC on a thickness measurement. The platform creates a decision task. Carlos reviews the photos, approves rework, and the lot goes back to In Production with the failed inspection preserved on the record. Two weeks later, the rework passes QC at 96% — the full history shows Attempt 1 (Failed, thickness), Attempt 2 (Passed). The lot moves to Packed, the released goods generate a shipment, and Carlos's monthly yield report shows Factory B's pass rate trended down 4 points this quarter — a conversation he'll have with them at the QBR.
WHERE IT FITS
Keep your inspection partner. Keep the factory's ERP. Run the production layer above them.
Most operators arrive with some tooling already in place — a third-party inspection service for incoming QC, spreadsheets for capacity planning, the manufacturer's own ERP for shop-floor work, sometimes an MRP for parts bought locally. TradeOS Production sits above all of it — running the operator-side production workflow that the existing stack doesn't cover. Nothing to rip out.
Manufacturer's own ERP / MRP
Stays where it is.
The factory keeps running their shop floor with whatever they use — bills of materials, work orders, machine assignment, line scheduling. None of that crosses the operator's workflow. TradeOS Production tracks the operator side: what the factory was asked to produce, what they confirmed, what came out of QC.
Third-party inspection services
Connects in.
If you use SGS, Bureau Veritas, Intertek, or a local inspector, their report drops into the lot record as photo evidence + structured data — AQL data for discrete goods, COA / lot-release data for bulk. The QC pass/fail decision lives in TradeOS; the inspector's job is the field work. Atlas reads the report and flags anomalies before you do.
Inventory / warehouse system
Receives the handoff.
When a lot is released, it flows out as finished goods ready to ship. If you operate a warehouse domestically, your WMS picks up at goods-received. TradeOS Production owns the upstream — the months between order and Released — that warehouse systems don't see.
Spreadsheets & messaging
Absorbed.
The capacity planning spreadsheet, the WhatsApp threads asking factories for status, the email chain about a thickness defect — all collapse into the lot record. The data was never meant to live in a spreadsheet; it just had nowhere else to go.
TradeOS Production
Runs the operator side.
Multi-manufacturer allocation by capacity and quality. Lots from creation through QC inspection to release. Sampling inspection with photo evidence and a formal rework loop. Yield tracking that affects real cost. AI-assisted allocation that proposes, never executes. One workspace for the production layer between PO and goods-received.
Generic MRP and shop-floor tools were built for manufacturers who own the line — not for the operator who buys from five factories across four countries. TradeOS Production fills the trade-specific gap: outsourced production management with QC as a first-class workflow inside the lifecycle, not a bolt-on. It doesn't replace your inspector or your factory's ERP; it runs the layer above them where the operator actually works.
FAQ
Frequently asked questions
Eight questions operators ask when evaluating TradeOS Production.
The Production module manages manufacturing across external factories. Trade operators use it to plan production by manufacturer and month, allocate quantities by capacity and quality, track production lots from creation through QC inspection to release for shipment, run AQL-based quality control with photo evidence and rework loops, and analyze yield and cost variance per manufacturer over time.
Bring us one of your production plans. We'll model it in TradeOS in 30 minutes.
The one with the QC fail, the rework lot, the supplier whose yield slipped, the factory that went on holiday in the middle of your peak. We'll show you what it looks like when allocation, QC, yield, and the rework loop are all on the same record. No demo data. Your data.