Industries
The approach doesn’t change with the industry. We go deepest in physical-goods supply chain and distribution: importers, distributors, manufacturers, freight, because that’s the operation we run ourselves. It carries just as well into healthcare, finance, and professional services, in English and Spanish, across the US and Latin America.
Tonnage, yield, and machine uptime live in field notebooks and separate systems, so a problem shows up after the shift or the season, not during it.
AI pulls scale, field, and maintenance data into one live read, flags equipment before it fails, and reconciles tonnage against contracts as it moves.
Assets, crews, and work orders are tracked across portals and email, so a missed inspection or a late part becomes a shutdown before anyone sees it coming.
AI watches asset and meter data for the early signal, schedules crews and maintenance against real constraints, and keeps compliance evidence audit-ready.
The floor runs on tribal knowledge and spreadsheets, so a wrong part, a stale BOM, or a critical-spare stockout stops the line and nobody knew until it did.
AI cleans the part master, turns a fuzzy request into the exact SKU, and reorders on real velocity so the line keeps moving.
Landed cost doesn’t exist until the broker’s invoice arrives and the margin is already gone, and one wrong HTS code holds the container.
AI reads supplier email and messaging threads for PO status, and computes landed cost per SKU at quote time, before the goods move.
Reorder happens when someone notices a low shelf on Tuesday, and one order-status question sends the team to four systems for a single answer.
AI sets reorder points from real velocity and lead time, matches every chargeback to its claim, and gives one answer per order from ERP, carrier, and inbox.
Shipment status is assembled from carrier portals, email, and phone by hand, and service load grows one-for-one with volume.
AI aggregates carrier and port status into one feed, pushes client updates on real events, and flags when a lane stops covering its cost.
Prior authorizations and denials pile up faster than staff can clear them, and lot, expiry, and cold-chain evidence scatter across sites until an audit becomes a scramble.
AI checks eligibility and drafts the prior-auth packet from the chart, routes each denial with the reason code read, and tracks lot, expiry, and cold-chain across every leg.
Month-end is a manual scramble across exports and spreadsheets, and past-due follow-ups go out when someone finds time, not when they’re due.
AI drafts collections with the right contact and amount, reconciles across systems, and assembles a clean close so the team reviews instead of builds.
The work is billable, but a third of the day goes to intake, document lookup, scheduling, and status updates nobody bills for.
AI drafts and retrieves from your own documents, runs intake and scheduling, and turns unbilled admin back into billable capacity.
Why us
Enterprise ERP in LATAM is sold as a multi-quarter project with per-seat pricing built in. We go live inside the operation you already run, before that project would have cleared discovery.
The engagement is sized to the operation, so hiring is never a penalty. Your whole team works in the system from day one.
Next.js + Supabase + Postgres, the standard stack. If we disappear tomorrow, any dev shop picks it up where we left off. With a legacy ERP, your data sits in a proprietary format and leaving means paying for a second implementation.
No account managers, no partner handoffs, no consultants billing by the hour. You work directly with the three founders, across engineering, operations, and finance. Every dollar goes to the work.
We don’t ask a client to run anything we don’t run ourselves, every day, on our own floor.
A 30-minute call, then a short audit inside your operation. The ranked plan is yours either way.