Tera Bullion builds supply chain visibility for CPG brands: end-to-end dashboards tracking inventory levels, supplier lead times, and fulfillment SLAs across the entire chain. The stockout you'd have discovered in a distributor email surfaces weeks earlier as a trend line — because the chain's problems were always visible in the data, just never in one place.
The worst supply chain problems don't announce themselves — they're discovered. The stockout you learn about from a distributor's email. The bestseller that sat at the 3PL for three weeks while its Amazon listing starved. The supplier whose lead time quietly stretched from four weeks to six, unnoticed until the PO that should have covered your best season arrived after it.
None of these were sudden. Each was visible in some system, weeks early, as a trend: inventory cover shrinking against velocity, a lead time drifting, an SLA slipping. But the data lived in five places — the commerce platform, the 3PL portal, the distributor's EDI feed, a supplier spreadsheet, someone's inbox — and no one place showed the chain as a chain. So a brand with good people and good systems still gets ambushed by problems its own data predicted. You're either sitting on dead inventory or stocked out during your best week — and often both at once, in different SKUs.
Carrying more safety stock is paying cash to not look. Buffer inventory blunts every surprise by burying working capital in all the SKUs that didn't need it — dead stock on the slow movers, and somehow still a stockout on the fast one, because the buffer was sized by rule of thumb instead of by visibility.
More check-in calls and portal logins turn your ops team into a manual polling system. Five logins, each showing its own silo in its own format, reconciled in someone's head — the labor repeats daily and the picture is stale by afternoon. Attention doesn't scale; pipelines do.
Trusting each partner to flag problems outsources your visibility to parties with their own incentives. The 3PL, the supplier, and the distributor each see one link and none owns your outcome. By the time a partner's email arrives, their problem has already become yours.
The common failure: every fix adds padding, labor, or hope where the actual gap is integration — the chain's data joined in one place, watched continuously, with the math done on cover and lead times instead of on gut.
Before: the chain's state lives in five logins and an inbox → problems are discovered when a partner emails → the team firefights a stockout that was visible six weeks earlier → and working capital hides in safety stock sized by nerve.
After: one dashboard shows the chain end to end → shrinking cover on a fast mover flags itself with reorder time to spare → the slipping supplier gets a conversation backed by their own trend line → and inventory decisions run on cover math instead of anxiety.
If you sell through more than one channel and your chain has ambushed you in the last year, this is the build that ends the ambushes — your own data, finally assembled into the one view that shows the chain as a chain.
Wherever data exists: inventory by location across warehouses, 3PLs, and channels; supplier and production lead times against their history; inbound purchase orders and their slippage; and fulfillment SLAs by channel. If a link in your chain records data — and nearly all of them do — it can feed the view.
Commerce platforms, marketplace and retail portals, distributor EDI feeds, 3PL and warehouse systems, inventory tools, spreadsheets that hold real data — if it exports, we can warehouse it. That's the same integration principle behind all our CPG builds: one source of truth across everything you sell through.
By watching cover, not counts. A quantity on hand means little alone; that quantity against current velocity and supplier lead time is weeks-of-cover — and when projected cover for a SKU dips below the reorder horizon, that's a flag while there's still time to act. The signal was always in your data; it just required joining three systems to see.
Yes — quoted versus actual lead times, by supplier, trended. The supplier that's quietly slipped from four weeks to six shows up as a line bending months before it becomes the stockout story. That evidence also changes the tone of the next supplier negotiation.
As current as your systems' feeds — for operational purposes, live. The practical shift is from finding out via a distributor's email or a 3PL's apology to seeing the trend yourself, weeks earlier, on a dashboard the whole team reads.
It's the natural pairing. Visibility tells you what the chain is doing; forecasting tells you what demand will ask of it. Brands typically start with the visibility layer, then add ML forecasting on the same warehouse — the plumbing is shared, so the second build is cheaper than the first.
Scoped to your channel count and systems, which is why we start with a free build plan rather than a rate card. Tell us where your chain has surprised you in the last year and we'll map the build against those exact blind spots.
Tell us how this works in your operation today. We'll send back a build plan — no pitch deck, no fluff, just engineering.
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