What does Neovara do?

Neovara is an AI & data partner for F&B, hospitality and other ambitious SMEs. We build and run AI agents that do the work — Agentic as a Service — on top of a clean, structured data foundation you can actually trust. Where it's useful, we run the back-office too.

What is GaaS, or Agentic as a Service?

GaaS stands for Agentic as a Service. With software — SaaS — you buy a tool and your team does the work inside it. With GaaS you get working AI agents that do the job itself: researching, processing, reporting, updating your systems. They're built around how your business already runs, and we manage them. You're buying the outcome, not the licence.

Do you specialise in F&B and hospitality?

Yes. F&B and hospitality is our home turf: we built and proved the model with fine-wine merchant Cru Wine — back-office costs down 65% and a record profit year. We also work with SMEs beyond F&B.

How do we start, and how do you price?

Start with the AI & Data Health Check: a fixed-price, two-week diagnostic that scores your data, maps your back-office costs and ranks your top five AI opportunities in AED. Or book a free 20-minute discovery call first. Everything after that is scoped to your business, not to a package. No long-term lock-in.

Do we need to replace our existing systems?

Usually not. Most of the value comes from connecting and cleaning what you already have, then putting agents on top. If something genuinely does need replacing we'll tell you — but that's rarely the first move, and it's never the starting point.

Where is your team based?

We deliver from four hubs: the UK, Philippines, India and Dubai.

What is the difference between AI enablement, data architecture and back-office support?

AI enablement gets your team using AI effectively; data cleaning and architecture builds a single source of truth you can trust; back-office support is our team running finance, IT, customer service, marketing and admin for you.

Do you only work with F&B and hospitality?

No — F&B and hospitality is where we go deepest, but we help any SME growing fast on messy data and manual back-office.

How can AI help my restaurant?

How can AI help my restaurant? Six back-office jobs it does well

Ask a UAE restaurant owner where AI fits and most will picture a chatbot taking bookings. Useful, but small. The bigger payoff sits behind the pass: in the hours your team spends matching delivery payouts, keying in supplier invoices and building a P&L that lands weeks after the month it describes.

The UAE isn't short of AI users. 70.1% of its working-age population used AI in the first quarter of 2026, the highest rate in the world, according to Microsoft's AI Diffusion Report, as reported by Gulf News. What most F&B businesses lack is AI pointed at the right jobs.

The short answer

AI helps a restaurant most where the work is repetitive, rule-based and full of data: reconciling sales across your POS and delivery apps, processing supplier invoices, flagging odd voids and refunds, answering questions about your numbers, forecasting demand and drafting the weekly report. It helps least when the data underneath is messy. So that's where to start.

1. Matching delivery app payouts to your POS

Talabat, Deliveroo and Careem each pay out on their own schedule, net of commission, promotions and refunds. Someone on your team has to match every payout back to the orders in the POS, outlet by outlet.

An AI agent can do the matching line by line and hand a person only the exceptions: the missing order, the refund that never came back, the promotion you didn't agree to fund. Your accountant stops ticking and starts checking.

2. Reading and matching supplier invoices

Supplier invoices arrive as PDFs, phone photos and email attachments. AI can pull out each line, match it to the purchase order and the goods received note, and flag a price that changed since last week.

This matters more than usual right now. Under the UAE's e-invoicing rollout, businesses with revenue under AED 50M must appoint an Accredited Service Provider by 31 March 2027 and go live on 1 July 2027 (KPMG, UAE Ministry of Finance). Getting invoice data clean and structured now is half of that job done.

3. Spotting leakage: voids, refunds and zero-value bills

When PAR Technology studied the questions operators actually ask AI tools, loss prevention was the biggest cluster. Back-to-back zero-value transactions on one cashier. Repeat refunds to the same card within 30 days. And the late-night classic: "Where am I losing the most money?"

A person checks a sample at month-end. AI can check every transaction, every night, and send the three that look wrong to the outlet manager by morning.

4. Answering questions about your numbers in plain English

"Which outlet's food cost jumped last week, and which dishes drove it?" Today that question goes to finance and comes back as a spreadsheet a few days later.

With your POS, inventory and accounts joined up, an AI assistant can answer it in seconds and show you the rows behind the answer. Owners ask more questions when answers are cheap.

5. Forecasting covers and prep

Demand forecasting is where AI meets the kitchen. Blue Bottle Coffee used it to predict daily pastry demand across more than 100 cafés, and its technology partner Provectus reports an 8% improvement in ordering accuracy in the first month. Café managers could still override the forecast with local knowledge, which is the right design.

For a UAE group, the same approach applies to prep lists, stock orders and rotas: weekends, school holidays, Ramadan and big events all show up in your sales history if the history is clean.

6. Drafting the weekly and month-end commentary

Numbers don't explain themselves. AI can turn a week's sales, food cost and labour data into a first draft: what moved, by how much, and what to look at next. Your finance lead edits a page instead of writing one from scratch.

What AI won't fix

If your POS item names don't match the recipes in your inventory system, or every delivery app lands in Xero as one lump sum, AI will give you confident wrong answers faster. That's the unglamorous truth: most of the work is getting the data right first.

It's work we know well. Neovara was proven on a loss-making fine wine business, which we turned into a lean operation: back-office cost down 60% and a record-profit year.

Where to start this month

Time the three back-office tasks that eat the most hours, for one normal week.
Pull last month's POS sales and delivery payouts and check whether they agree with Xero.
Check that outlet codes, item names and supplier names match across your systems.
Pick one high-volume job where a mistake is cheap to catch. Payout matching is a good first candidate.

If step 3 turns up a mess, our POS Data Unification Checklist walks you through fixing it, system by system.

Download the POS Data Unification Checklist

FAQ
Is AI worth it for a small restaurant group? Yes, if you start with a job that already costs you hours every week, such as payout reconciliation or invoice processing. Measure the hours before and after, and you'll know within a month.
Do I need to replace my POS to use AI? No. The jobs above work with data from the systems you already run, as long as that data is consistent across them.
What should I fix before buying an AI tool? Your data. Make sure sales, stock and accounts use the same outlet codes, item names and supplier names, and that delivery app income is recorded by platform and outlet.