Food & Beverage · QSR order automation
A wrong order at the pass is a failure the system could have caught
Banao builds AI order automation for QSR chains — voice capture at the drive-through, accuracy checks before a ticket prints, upsell logic trained on your own basket data, and kitchen display routing that keeps ticket times flat when the lunch rush hits.
Every component integrates with your existing POS and KDS. You keep your stack; we wire in AI where the order errors and queue times are actually being built.
The first call is free · 45 minutes · no obligation
What we build
What a Banao QSR order automation deployment includes
Each component targets a specific point in the order flow where a mistake or a delay is costing you margin. We build what fits your flow, integrated into your POS.
Voice order capture at the drive-through
An AI voice agent that takes the order, confirms it back, and passes a structured ticket to your POS — trained on your menu language and your customers' phrasing, including specials, upsizes, and modifications.
Order accuracy check before the ticket prints
The system reads the full ticket and flags mismatches — a modifier attached to the wrong item, an incompatible combination, an item that is 86'd — before the kitchen ever sees it.
Upsell engine trained on your basket data
Prompt logic built from your own transaction history: what actually sells alongside what, at which daypart, and at which price point. Built on how your customers order, not a generic upsell script.
Kitchen display and ticket routing
Ticket distribution across stations weighted by current load and prep time, so the fry station doesn't back up while grill sits idle. Integrates with your existing KDS where an API exists.
Drive-through queue and wait-time modelling
A model over camera or sensor data that estimates queue length and wait time per vehicle, manages expectations at the speaker, and surfaces the pattern to operations when it repeats.
POS and reporting integration
Every order, correction, and upsell event writes back to your POS and reporting layer. Operations and franchise teams see order accuracy rates, average ticket value, and queue times in one place.
Dogfooding
We operate on the AI we build before you do
Banao runs a ~300-person engineering company on its own AI products. InterviewGod screens our own hires. Vikaas runs our own demand-gen pipeline. A system that has to survive internal load is already stress-tested before any client sees it.
When we build a voice ordering agent or an accuracy check, it has already been through the kind of edge-case pressure a real service produces — not just a test dataset.
Screens Banao's own engineering hires every week.
Runs Banao's own demand-gen pipeline end to end.
The honest version
When QSR order automation is the wrong build
Most vendors will spec an order automation platform regardless of whether your bottleneck is at the order-capture step. We will tell you when it isn't:
- Low order error rate: if your current accuracy is already above 98%, the margin problem is probably in prep time or staffing — not capture. We map the real constraint before recommending a build.
- Thin POS API: if your POS has no documented integration path and a vendor lock that prevents it, the integration cost often exceeds the cost of the errors you're fixing. We scope this honestly before you commit.
- Drive-through not the bottleneck: if your wait times are built in the kitchen rather than the capture step, an order AI shortens queues by a minute at most. A kitchen ops model is the right call instead.
How we start
How we start — see the ROI before you build
You have seen order automation vendors quote a platform before seeing your ticket data. We look at your actual order flow first.
- 01
AI Discovery Sprint
2 weeks · fixed price
We audit your order error data, ticket times, and basket composition, identify where AI closes the gap, and produce a component-by-component ROI model — yours to keep. If you proceed, the Sprint cost is credited against the build.
- 02
Build
POS and KDS integration first, then the model. Voice agent, accuracy check, upsell logic, and routing are each scoped to your flow and your hardware — not a generic template.
- 03
Production & continuous tuning
Deployment with dashboards showing order accuracy, upsell rate, and queue time per site, plus ongoing model tuning as your menu and order patterns evolve.
FAQ
Frequently asked questions
Will it work with our existing POS?
We integrate where a documented API or export exists — which covers the major QSR POS platforms. Where it doesn't, we assess the integration path in week one and tell you the real cost before you commit. We don't assume integrations we haven't confirmed.
How does the voice agent handle accents, background noise, and unusual orders?
It is trained on your menu vocabulary and refined through a warm-up period on real orders at your sites. Where the agent isn't confident — a complex modification or an unclear request — it escalates to staff with the partial order captured, not a blank screen.
How do you measure order accuracy if we don't track errors today?
We start from what you do have: remake tickets, void transactions, customer complaint codes, or a short structured observation period at the counter. The Discovery Sprint is designed to work with imperfect data, not to wait for perfect data.
Can one site run a pilot before a full estate rollout?
Yes — a single pilot site is the standard starting point. It is where the integration is confirmed, the voice model is tuned to your customer base, and the accuracy and queue metrics are established before a broader rollout is costed.
How does the upsell model differ from the prompts already in our POS?
Static POS prompts are time-averaged guesses. Our upsell engine is trained on your own transaction history — what actually adds to basket, at which daypart, for which anchor item — and is retrained as your menu and seasonality change.
Get started
Bring your order error data and your drive-through queue times
In 45 minutes we'll show you where AI closes the gap in your QSR order flow — and what the ROI numbers look like before you build anything.
Book a Discovery Sprint