When the chain has fifty stores and each one feels like a different country.
The software that runs a Latin American grocery chain isn't a system. It's an agreement between seven systems — ERP, POS, e-commerce, app, marketplaces, bank reconciliation, cold chain — that age at different rates. FastNet doesn't replace the agreement. We operate it, extend it, and modernize it without throwing away what already works.
The body of your chain.
The typical chain we serve runs this stack: legacy ERP (SAP IS-Retail, Oracle Retail, JD Edwards or a twelve-year-old custom build), multi-store POS with batch sync, e-commerce on Magento or VTEX keeping its own "almost"-synced inventory, retailer mobile app, integrations with local marketplaces (PedidosYa, Hugo, Uber Eats), end-of-day bank reconciliation across four or five banks, an IoT-based cold chain system, and a handful of Excel sheets propping up critical processes.
Each of those systems was chosen for valid reasons in its moment. None was designed assuming it would have to talk to the other seven in real time. That's the operational reality. The right question isn't how do we migrate. It's how do we build the space between the systems correctly — without breaking fifty stores' operations while we build it.
What's hurting today.
Migrating the ERP costs USD 800,000 to 4 million depending on scope. Nobody wants to sign that, and rightly so. But the team hears the same questions every Monday: 'why did the web sell a product without stock?', 'why is bank reconciliation still manual?', 'why was the cold room at the San Pedro branch at 8°C overnight and nobody noticed?'.
Those aren't ERP problems. They're problems of the space between the systems — the layer historically nobody designs because nobody bills for it. The good news is that this layer, built well, ships in 90 days without touching the ERP. The better news is that the same layer opens the path to serious observability, applied AI with ROI, and gradual modernization without continuity risk.
The ecosystem that grew by accretion, not by architecture.
There's a pattern that doesn't appear on any architecture diagram. We see it in chains with hundreds of stores, multiple operating formats, and decades of accumulated technical history.
A chain with decades of technical history doesn't have a system. It has an ecosystem that grew by accretion. Each module entered through a valid decision at the time — one vendor sold accounting, another HR, another POS, another promotional analytics, another bank gateway. Today they all talk to each other, almost all of them. And when something new has to be added — gift-card reading at the register, an integration with one more bank, a bakery module with recipes and waste tracking — the technical conversation starts, without exception, with the same sentence: "that requires touching seven systems".
The industry typically responds in one of two ways. The first: bring in a large consultancy to propose a unified platform — three-year project, seven-figure budget, operational continuity risk. The second: add one more module to the ecosystem with duct tape. Neither solves the problem. The first is too ambitious for a business that can't stop. The second perpetuates exactly the condition you wanted to change.
Modernizing a decades-old ecosystem isn't a sprint — it's a sustained effort with cadence. What actually works is entering surgically through a small piece that meets three conditions: isolable today, with a bounded blast radius, and built on a new architecture that can grow. Measurable ROI in 90 days, not three years. When that piece works, the next conversation comes naturally: "can we do the same with the inventory module?". The answer is yes, because the new architecture is already there. What started as a small module becomes the base on which the next ones grow — next to the existing ecosystem, not on top of it.
The legacy system keeps running until certain modules stop being queried — not because of a big decision, but because the new architecture already covers what they did. It's the only honest way to modernize a decades-old ecosystem without asking the business to pause its operations, and the only way the internal team gains the space to focus on what really needs new architecture: applied AI, predictive analytics, real-time operations. Technical debt gets paid down, module by module. Zero traumatic maintenance windows. Zero continuity risk.
What we design in this vertical.
We don't sell platforms. We design and operate the pieces your chain needs. Four kinds of project we actually move in grocery enterprise:
Event-driven middleware over your existing ERP
Apache Kafka or Redpanda + Debezium for CDC, NestJS/FastAPI with idempotent consumers, Avro schema registry. The ERP doesn't notice. Modern systems stop depending on it. Any future system plugs in without touching anything existing.
Observability stack calibrated for 50+ stores
OpenTelemetry as the open standard, Grafana Cloud for metrics/logs, Tempo for traces, MQTT + InfluxDB for cold chain, alerting with clear hierarchy. POS by store with criticality weighted by hour, day, and seasonal peak.
Applied AI with measurable ROI
Demand forecasting with local features (Central American operating calendar, weather, neighborhood events, competitor pricing). Semantic search that resolves Spanish regionalisms ("blanquillos" → "huevos") on pgvector. Scoped RAG assistant for store managers with explicit fallback.
Integrations with local marketplaces
PedidosYa, Hugo, Uber Eats — each with its catalog format, order webhook, stock policy. One event topic, marketplace-specialized consumers, idempotency throughout, dead letter queue as standard. What breaks on a peak holiday night breaks once.
Default recommended stack.
When no internal legacy stack constrains us, this is what we apply:
Cost math, no makeup.
Building this team in-house in Latin America is expensive and slow. A senior platform engineer with grocery experience runs USD 90,000 to 130,000 per year (Central America) or USD 180,000+ (Mexico). To do this well you need at minimum: 1 senior, 1 mid, 1 part-time SRE, 1 technical PM. With burdens, the team costs USD 240,000 to USD 400,000 annually — before counting recruitment time (4 to 6 months for senior profiles) and turnover risk.
Our enterprise retainer for grocery covers the operational equivalent from USD 12,000 to 20,000 monthly, with team composition defined per deliverable. Over 12 months that represents 60% to 70% savings versus an in-house team, without recruitment friction or sunk cost if project pace changes. If you want to bring the team in-house after year one, we transfer knowledge and stay as a second line on hours — no markup.
There is no "loose hourly" model. The reason is operational: loose hours kill margins and make architecture impossible to plan. Explicit trade-off.
Pre-reading, before the call.
If you want to size up how we think about the problem before we talk, the three technical posts are honest reading — no pitch, no gated content.
If you run technology at a 50+ store chain, let's talk.
Thirty minutes. No slides — we listen to how the agreement between your seven systems is actually built and come back with an honest map of what to modernize first and what can wait another year. Even if you decide afterwards to do it in-house or with another agency, you keep the map.