Public Safety

alertahora.app

Crime detection + news scraping service covering 50+ sources in Colombia.

50+

Sources monitored

500+

Reports/day

10K+

Active users

The Challenge

Product team needed real-time crime feeds without adding headcount.

The Solution

How We Solved It

Built FastAPI services and n8n jobs that scrape news, classify incidents, and push alerts into their app.

Automated Workflows

Real-time Monitoring

Seamless Integration

Scalable Architecture

Role

AI Automation Engineer

Audience

Public Safety Companies

Timeline

4-6 Weeks

Tools

FastAPIn8nPythonPostgres

Understanding the Problem Space

Through comprehensive analysis of alertahora.app's operations, we identified key bottlenecks and inefficiencies. The manual processes were not only time-consuming but also prone to errors, creating a significant drag on productivity and scalability.

Automation Overview

Real-time monitoring of all automated workflows

50+

Sources monitored

500+

Reports/day

10K+

Active users

Workflow StatusActive

Real-time monitoring of all automated workflows

Key Insights

•Manual processes were consuming 40-60% of team time on repetitive tasks
•Error rates in manual workflows were significantly higher than automated processes
•Scalability was limited by human capacity, not system capabilities
•Team members were eager to offload routine work to focus on strategic initiatives

Technical Implementation

Translating Insights into n8n

We translated our research insights and design principles into concrete n8n workflows. Each workflow was carefully architected to be maintainable, scalable, and aligned with business objectives.