How QueryAlerts works
QueryAlerts combines a local agent with a SaaS dashboard to automate queries, detect important events, and deliver notifications without exposing the customer database.
First, the problem most operations already have
In many companies, someone needs to open the ERP or database every day to check for delayed orders, inactive customers, invoices nearing due dates, low stock, or missed targets. That follow-up often depends on memory, spreadsheets, and manually running queries throughout the day.
The problem is that when the routine depends on human checking, the team only notices what happened after the delay already exists, the customer has already cooled off, or the team has already lost time reacting late. QueryAlerts is designed for exactly that gap: it turns recurring checks into automatic, actionable alerts.
A simple example to make it concrete
Imagine a sales operation that needs to identify every day which VIP customers have gone 48 hours without placing an order. Without automation, someone needs to remember to run the query, review the results, and notify the sales reps. With QueryAlerts, that logic is configured once and then runs automatically on the chosen schedule.
If the query finds customers in that condition, the platform records the execution and sends the alert by email or WhatsApp to the people who need to act. The same logic applies to blocked orders, upcoming receivables, low stock, revenue below target, and other operational scenarios.
- Customers without a recent purchase
- Delayed or blocked orders
- Stock below minimum level
- Sales targets below expectation
Agent installation
The agent is installed in the same environment as the customer database or in a server with internal access to that database.
- Windows and Linux installation
- Runs as a service
- Simple local setup flow
Query execution
Queries published in the dashboard are synchronized to the agent. The agent runs each query on schedule and evaluates whether a notification should be triggered.
Notification delivery
After the agent sends the result, the SaaS records the execution and delivers notifications by email, WhatsApp, or both, depending on the query configuration.
How the day-to-day flow works
In practice, the team creates the query in the dashboard, defines the execution interval, chooses recipients, and publishes it. From that point on, the local agent pulls the configuration, runs the query on schedule, and sends the result back to the platform.
If the query returns a situation that requires attention, QueryAlerts records the event, keeps execution history organized, and delivers the message through the selected channel. This reduces dependency on spreadsheets, manual checks, and follow-up routines based on memory.
- Query setup in the dashboard
- Automatic sync with the local agent
- Recurring execution inside the customer environment
- Centralized execution and alert history
Operational benefits
The main benefit is turning SQL into an actionable operational routine. Instead of someone opening the ERP, running reports, and looking for exceptions, the system identifies relevant scenarios and sends the alert directly to the people who need to act.
This helps sales, finance, support, logistics, and management teams respond faster to delays, missed targets, inactive customers, blocked orders, and other situations that should not wait for manual analysis.
- Less dependence on manual follow-up
- Faster response to operational exceptions
- Real-time visibility for managers and teams
- Consistent alert workflows across different areas
Why this model works well
The local-agent-plus-SaaS model keeps responsibilities clearly separated. Sensitive database access stays inside the customer environment, while the dashboard centralizes queries, schedules, history, and notifications.
That makes implementation simpler for IT and daily usage clearer for business teams. The result is a more predictable operation, with less delay in identifying problems and more consistency in tracking important indicators.
Ready to turn queries into alerts?
Create your account, connect the local agent, and publish your first queries without exposing the customer database.