Data Panda brings your ERPNext data together with the data from the rest of your business. From one place, we turn it into dashboards, automations, AI workflows and custom apps your team uses every day.
ERPNext was started in 2008 by Rushabh Mehta and is built by Frappe Technologies in India. It runs on the Frappe Framework, a Python and JavaScript stack with MariaDB underneath, and the whole thing ships under GPL-3. That matters: ERPNext is one of the few production-grade ERPs where the source is fully open, the data model is yours, and your team can extend it with new DocTypes without buying a separate platform licence.
Most ERPNext shops live on Frappe Cloud or self-hosted, with strong adoption in India, Southeast Asia and a growing footprint across the EU and North America. The point of pulling ERPNext into a warehouse is not that ERPNext lacks reports. It is that the questions worth asking cross modules and systems: stock turnover versus accounting reconciliation, the App-Store-installed module versus core ERPNext, ERPNext versus the webshop, ERPNext versus the CRM the sales team relies on day to day. Those questions end up in spreadsheets, and the spreadsheets always lose to the next Frappe upgrade.
One picture of stock, accounting, sales and manufacturing instead of four ERPNext print formats stitched together.
Keep ERPNext in sync with the systems that live around it, without writing another Frappe hook for every pair.
Turn ERPNext history into forecasts and scoring on data your team already trusts.
Small tools on top of ERPNext data for people who should not have to learn the Desk.
A list of concrete reports, automations and AI features we have built on ERPNext data. Pick the one that matches your situation.
Why does the stock value never quite match the GL?
Stock ledger value next to the inventory GL balance, day by day, with the variance broken by item group, warehouse and posting date. The customisation, the late stock entry or the missing landed-cost voucher driving the gap shows up by name, not as a month-end reconciliation header.
Which products are quietly killing margin after taxes and discounts?
Gross margin per item over time, after purchase cost, freight, applicable taxes and the discount stack from pricing rules. Slow-moving items and discount-heavy SKUs are ranked together, so reorder decisions stop relying on revenue alone.
How long between a sales order and a paid invoice?
Sales order date to delivery note to sales invoice to payment entry, per customer and item group, with elapsed days at each hop. The hop where the cycle stretches becomes obvious, instead of being averaged out in a single days-sales-outstanding number.
Group consolidation across ERPNext companies, AR and AP aging next to cash, and a stock-versus-GL tie-out that does not wait for the month-end reconciliation. The variance lands on the dashboard the day it happens, not in the close week.
Quote-to-order-to-cash velocity per rep, territory and item group, with stock availability and credit limit visible at quote time. Sales stops promising delivery dates the warehouse cannot keep.
Stock turnover, BOM cost variance and supplier lead time in one picture. The custom DocTypes the team built for the shop floor join back to standard ERPNext data, so site reports survive the next Frappe upgrade.
Shopify orders land in ERPNext as sales orders with the right items, warehouse, taxes and pricing rules. Stock entries and delivery notes follow, and refunds post as credit notes. Inventory stays in one ledger and the webshop sits in the same P&L as the rest of the business.
Stripe charges, refunds and payouts flow into ERPNext as payment entries and journal lines, matched to the right sales invoice and customer. Bank reconciliation runs on real bookings instead of a Stripe export, and finance sees fee, FX and chargeback impact at the customer level.
HubSpot deals that reach closed-won create draft quotations or sales orders in ERPNext, with customer and contact records aligned. Order status, delivery and invoice state flow back to the HubSpot deal, so sales sees the fulfilment side without logging into the Desk.
ERPNext delivery notes create Sendcloud shipments with the chosen carrier, service level and parcel data. Tracking codes and delivery status flow back to the delivery note and the linked sales order, so customer service answers a where-is-my-order question from one screen.
You keep the reporting tool you already have. We connect it to the warehouse where your ERPNext 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.
Custom DocTypes, custom fields and the data behind site-specific Frappe apps come across as first-class tables and columns in the warehouse. The warehouse model captures what each field meant at the time it was used, so reports keep working when a DocType is renamed, refactored or migrated to a new module in a later Frappe version.
Yes. Frappe Cloud and self-hosted ERPNext both expose the same Frappe REST API and the same MariaDB schema underneath. We connect via REST for incremental sync where it is fastest, and read directly from the database for historical extracts and large reporting tables. The warehouse schema is the same either way.
We review your ERPNext setup and the systems around it. Together we pick the first thing worth building.