Cultura Açaí, Rogers Smash Burgers and Pardos Chicken run on transaction codes, fixed reports and terminal-era software. Clave made those systems feel plug and play.
Sales, inventory and waste hidden behind transactions built for specialists.
Back-office software that feels frozen before the modern web.
Systems that are not publicly accessible and sit behind private VPNs.
Generic AI assumes a clean world: every company has a modern data warehouse, an MCP server, an API key and an engineer ready to wire it all together. It works beautifully after someone else has finished the hard connection work.
That is not how restaurant operations work. Restaurant groups often rely on country-specific accounting platforms, local vendors, terminal-era back offices and software that global AI companies were never built to recognize. Some of it is not web-hosted at all and can only be reached through private VPN tunnels.
Clave imagined a world where connecting restaurant data really was easy: pick the systems, connect them, start asking questions. Then Clave fought tooth and nail to build that world. If SAP R3, NCR NBO, Restaurant PE, Contífico and terminal-based applications can feel simple across Peru and Ecuador, restaurant systems anywhere can.
“I was surprised you could get information out of that system. We thought there was nothing better.”
A reaction repeated across Pardos Chicken, Rogers and Cultura Açaí
An AI answer is only as good as the data, definitions and operating context behind it. Clave builds an ontology for each restaurant group: the brand's stores, products, modifiers, channels, suppliers, financial definitions, roles, recurring reports and operating rules.
A sale is not just a sale. It may belong to a specific store, channel, country, daypart, product family or promotion. A modifier may be free by design or incorrectly priced. An empty store may be closed, not underperforming. A change to average ticket can make an entire recurring report wrong.
The agent needs to understand those differences before it can be useful. The operator still sees one place to ask questions, run reports and decide what to do next.
Pardos Chicken runs 30 restaurants in Peru on SAP R3, Restaurant PE and NCR Back Office. The raw system language is not built for an operations manager: sales sit in ZPISD002 Reporte LOG, inventory uses MB5B, waste appears in MB51 movement types 971 and 972.
In one week, Clave mapped the data behind Pardos’s sales, inventory and waste workflows. The goal was never to make the team learn transaction codes or rebuild reports from exports. It was to make those systems useful in the language of restaurant operations.
Instead of navigating SAP, NCR Back Office and separate restaurant platforms to reconstruct an answer, a manager works through Clave. The systems stay in place. The operating work gets easier.
Cultura Açaí uses Contífico, an Ecuadorian accounting platform that plays a QuickBooks-like role for many local teams. Connecting it is the beginning. The work that matters is making sure the agent understands the menu, the store logic and the daily operating definitions.
Cultura’s menu data included toppings recorded as $0 modifiers. Clave found 12,461 topping uses in one month and turned it into an operating question: are these intentionally free, or is the business leaving money on the table? The same catalog work caught duplicate naming between "ACAI BOWL GRANDE" and "BOWL GRANDE."
When the owner challenged an average-ticket calculation, Clave corrected the logic, resent the report and carried the approved definition into future runs. A location with zero sales was recognized as permanently closed, not as a demand collapse or a broken feed.
Rogers Smash Burgers in Ecuador also runs on Contífico, and its team uses Clave from WhatsApp, where a normal operating question quickly becomes a decision.
A manager asks about yesterday’s sales. Clave compares stores, separates the channels, identifies what changed in product demand and turns that answer into the raw-material purchase the team needs to make next. The agent does not stop at a chart.
The operator never has to think about Contífico as a data source, a report as a separate job or WhatsApp as a disconnected channel. It is one operating conversation, grounded in the brand’s stores, menu and materials.
The restaurant industry has great operators running important work on systems that were never designed to talk to one another, never mind work with AI.
Clave meets them where they are. It builds the brand-specific knowledge that makes the data trustworthy, works with the systems the team already has and gives operators one agent that speaks restaurant.
No MCP fantasy. No assumption that every team has a clean API key waiting around. Clave fought through the hard connection work so using restaurant AI can finally feel plug and play.
