Logistics & Operations · Restaurant Tech
We developed a SaaS platform to centralize sales, accounting, and inventory data, providing a single source of truth for hospitality operators.
Outcome
3 data sources normalised; margin drops become tasks priced by what fixing them is worth.
The hospitality industry operates on thin margins where success depends on precise control over costs and revenue. Most restaurants and bars rely on a disconnected set of tools for daily operations, creating data silos that obscure the true financial health of the business.
The founding team of this B2B SaaS platform identified this fundamental friction. A manager might use one system for point-of-sale, another for accounting, and manual spreadsheets for inventory. This fragmentation makes it nearly impossible to see the direct financial impact of an operational choice, such as changing a supplier or adjusting a menu price.
They engaged Robust Devs to build the central intelligence layer that would solve this problem. Our work involved architecting a system that could ingest, normalize, and analyze data from multiple sources, turning raw information into clear financial insights and actionable directives.
The challenge
How we solved it
Technologies
The platform’s central catalog allows a business to map countless product name variations from different suppliers and point-of-sale systems to a single, authoritative item. This creates a definitive record for each product, enabling precise tracking of stock levels, accurate cost-of-goods calculations, and clear insight into waste and profitability per item.
Instead of simply presenting data, the platform actively monitors performance against set targets and industry benchmarks. When a metric deviates-such as labor costs rising above a certain threshold-the system automatically generates a task for the relevant manager, outlining the issue and its calculated financial impact. This connects data directly to action.
How we built it
Solved the product-name problem first, because no margin number is right until 'Coke' and the supplier's SKU are the same item. A POS, a supplier invoice and an API all describe the same product differently, and that mismatch was what made inventory analysis untrustworthy. A global product mapping engine lets operators link every supplier and POS description to one master product, and the Laravel pipeline normalises the three sources into a single dataset on top of it. From there, a task engine watches the metrics and, when a menu item's margin drops, creates an operational task priced by what fixing it is worth, so staff act on the most valuable problem rather than the most visible one.
In the client's words
“You're doing very, very well... the confidence that you're building with me, the full product is what I want to go with.”
Tell us what you're building. We'll show you how we'd approach it and what it would take to ship.