Data Panda pulls your Toast data and brings it together with the rest of your restaurant stack. From one place, we turn it into dashboards, automations, AI workflows and custom apps your operations, finance and marketing teams use every day.
Toast is a restaurant-purpose-built platform that bundles a POS, online ordering, delivery integrations, payments, payroll, gift cards, loyalty and supplier purchasing under one operator account. The cloud back end runs on tablets in the dining room and in the kitchen, and the company reports more than 120,000 restaurant locations live on the platform across full-service, quick-service, multi-unit and enterprise operators.
For ops, finance and marketing leaders, Toast is the system of record for the things the rest of the stack never sees: order checks with item, modifier and discount detail, payments split between dine-in, online and third-party delivery, employee shifts and tips with the pool rules applied, menu and item performance per location, and supplier purchase orders through Toast Supply. The built-in reports cover the day-to-day. The harder questions, like which menu items carry margin after promo and waste, how labour ratio drifts across day-parts, or which locations leak the most on void-versus-comp, sit across Toast and the systems around it. Pulling Toast into a warehouse is how those answers stop being a Monday-morning export.
Order, payment, menu and shift data joined to the accounting and marketing numbers the rest of the business already trusts.
Turn order, payment and shift events into the postings and nudges your team would otherwise do by hand.
Use order history, weather and shift patterns to forecast demand and tighten the schedule.
Small operations, finance and marketing tools that sit on Toast data instead of another spreadsheet.
A list of concrete reports, automations and AI features we have built on Toast data. Pick the one that matches your situation.
Which menu items carry margin after promos, waste and third-party delivery commission?
Item-level margin worked out from order checks, modifier choices, applied discounts and the commission third-party platforms keep, rolled up per location and day-part. The chef sees which signature dish quietly stops paying its way once delivery commission is taken out, and finance gets a menu-engineering view that is not a snapshot from January.
Where is our labour ratio drifting and which day-parts are the problem?
Labour cost from Toast Payroll-style shift data joined to the net sales those shifts produced, split per location, day of week and day-part. The operations manager sees the Tuesday-night dinner block that runs at 38% labour while every other shift sits in target, instead of finding out at month-end.
Which employees and locations have void and comp patterns that look unusual?
Voids and comps tracked per employee and per manager against the location baseline, with the time of day, the order check size and the reason code attached. Loss-prevention and the GM see the outliers in time to have a conversation, instead of after the next inventory variance puts a number on it.
Daily sales, taxes, tender mix and tip liability per location land in the accounting ledger nightly, and third-party delivery commission is booked as a real cost line instead of being lost in net deposits. Month-end stops being a reconstruction job.
Loyalty members, online-ordering guests and high-frequency repeat tickets become a single guest view that marketing can segment on. Promo planning runs on what guests bought, not on what last quarter's email open rate was.
Labour ratio per day-part, void and comp rate per employee and location, plus channel mix on the same dashboard. The Monday morning call is about which location and which shift to fix, not about whose export is right.
Each night, Toast sales, sales tax, tender mix, tips owed and third-party delivery deposits per location land in QuickBooks Online as the right journal entries, with delivery commission split out as a separate cost line. The bookkeeper stops rekeying the daily sales summary and finance closes the month on numbers that already match the ledger.
Toast item-level sales per location are joined to the recipes, sub-recipes and waste logs Apicbase holds, so theoretical food cost lands next to actual sold mix on the same report. The chef and the purchasing manager see plate-level margin drift before it shows up as an inventory variance two weeks later.
Loyalty members, online-ordering guests and repeat ticket holders flow into Mailchimp with the visit cadence, average ticket and last-ordered item attached. Marketing segments on what guests bought, so the promo email goes to the right cohort instead of the full list.
Threshold events from Toast data (a location running above target labour ratio at 7pm, void rate spiking on a shift, online ordering channel dropping mid-service) land in the right Slack channel for the area manager and the GM. Issues get a response during service instead of being read about the next morning.
You keep the reporting tool you already have. We connect it to the warehouse where your Toast data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
Toast tags each order with its channel of origin, so dine-in checks, first-party online orders and third-party platform orders (Uber Eats, DoorDash, Grubhub through Toast's integrations) come into the warehouse as distinct streams. Channel mix, average ticket per channel and the commission third-party platforms keep all become a query rather than a manual reconstruction.
Yes. Employee shifts, tips collected per check and the pool rules applied at close are pulled into the warehouse with the order and payment they tie to. That makes labour ratio per day-part, tip-share reconciliation and tip-credit reporting answerable from one source instead of stitching a Toast Payroll export to a sales export.
Each Toast location lands in the warehouse as its own dimension on orders, payments, menus and shifts, with the location's tax setup and menu version preserved. Group reporting joins them on date, day-part and menu item, so per-location performance and group-wide KPIs sit in one report instead of a stack of per-location exports.
We review your Toast setup and the systems around it. Together we pick the first thing worth building.