ERPNext ↔ WhatsApp Integration
Transactional messaging and operational alerts tied to ERPNext events - with delivery evidence, queue-safe sending, and audit-grade traceability.
Why ‘sending WhatsApp’ becomes a production problem
In production, messaging is not about sending. It’s about proving delivery, preventing floods, handling failures, and linking evidence to business documents.
Without delivery evidence tied to ERP documents, finance and operations cannot resolve disputes efficiently.
- Customers claim they never received invoices/receipts/reminders.
- Teams forward screenshots instead of using system evidence.
- No traceability from a message back to the source document.
A naive integration spams the provider, drops messages, and hides failures in background jobs.
- Bulk messaging causes rate-limit throttling and unpredictable delivery.
- Background failures are missed until customers complain.
- Retries can create duplicate notifications without guardrails.
Queue-safe delivery with evidence trails
This integration treats WhatsApp as an operational rail: trackable, auditable, rate-limited, and linked to ERPNext events and documents.
Each message has a status lifecycle (queued → sent → delivered/failed) with reason codes and references back to ERP documents.
Messages are sent through controlled queues with throttling to avoid floods, bans, and silent drops during peak traffic.
Retries are deliberate and traceable. The system avoids duplicate “spam” retries and preserves a clean audit trail of what was attempted.
What it does in ERPNext
We focus on business-critical messaging: transactional documents and operational exceptions.
Send ERPNext documents via WhatsApp and keep evidence of delivery linked to the originating document.
- Invoices, receipts, statements, reminders, delivery updates.
- Evidence trail linked to the exact ERP document (Sales Invoice, Payment Entry, Delivery Note, etc.).
- Templates and controlled formatting to keep messaging consistent.
Route operational alerts to specific teams so failures don’t sit unseen in logs.
- Payment exceptions, posting failures, stock anomalies, pending approvals.
- Alerts targeted by role/team (finance, ops, dispatch).
- Throttle controls to prevent alert storms.
A message system is only useful when it’s operable. We surface delivery status and failures in a way teams can use.
- Status lifecycle: queued, sent, delivered, failed - with reasons.
- Search and filtering by document, customer, time, and status.
- Evidence payload retention for support and audits.
Messaging must be controlled: who can send, what can be sent, and how failures are handled.
- Role-based access to sending and templates.
- Rate limiting and batching to respect provider limits.
- Safe retry policies to avoid duplicate customer notifications.
The messaging realities we design for
WhatsApp messaging in production is constrained. The integration is designed for those constraints, not against them.
Delivery can be delayed. Status tracking and evidence help teams respond calmly and correctly.
Providers throttle. We design for controlled queues so you don’t get bans or silent drops.
“It failed in the background” is not acceptable. Failures are surfaced to teams with context.
How we implement without spamming customers
We start with controlled transactional messages, prove evidence and reliability, then expand into alerts and broader messaging.
Set templates, link evidence trails, and enable controlled sending for core documents.
- Pick the first documents (Invoice, Receipt, Statement, Delivery).
- Define template rules and recipient mapping per document.
- Enable message logging + status tracking + safe retries.
Add targeted alerts and scale throughput with throttling and queue controls.
- Enable operational alerts (exceptions, failures, anomalies).
- Configure team routing and alert throttling.
- Introduce batching/rate limiting tuned to your volume.
Want WhatsApp messaging you can prove and operate?
We’ll review your documents, customer touchpoints, and internal alert needs - then propose a rollout that keeps delivery evidence, respects rate limits, and avoids silent failures.