🤖 From Manual to Magical: How We Automated Entire Workflows Using APIs, Webhooks & Queues

Manual work kills momentum.

Every day, teams waste time:

• Copy-pasting data between tools
• Manually updating reports
• Chasing status updates across platforms
• Writing one-off scripts for recurring jobs

We've helped dozens of clients automate these pain points, turning hours of grunt work into real-time, scalable pipelines using:

• ✅APIs
• ✅Webhooks
• ✅Cloud Queues
• ✅Cron jobs
• ✅Serverless functions

⚙️ Real Automation Use Cases We've Built

🔹 1. Jira Ticket Automation from Form Submissions

Problem: Product managers had to manually create Jira tasks from bug forms.

Our Solution:

• User submits form → Trigger webhook
• Serverless function creates Jira issue with details
• Sends confirmation email and Slack alert

Tools Used: Google Forms → Webhook → Cloud Function → Jira API → Slack

🕒 Saved ~5 hours/week in ticket handling.

🔹 2. Figma → GitHub Commit Tracking

Problem: Designers wanted to know when their designs were implemented.

Our Solution:

• Used Figma API webhooks for node updates
• Tagged Jira ticket + design ID
• Parsed GitHub commit messages for Figma refs
• Created a timeline view from Design → Dev → PR

📈 Improved design-to-release visibility by 90%.

🔹 3. Real-Time Facebook Ads Dashboard

Problem: Marketing team manually checked ad insights daily.

Our Solution:

• Used Meta Marketing API on a schedule
• Synced data to Firestore + BigQuery
• Auto-refreshed a dashboard with spend, reach, and ROI
• Alerted if ad CTR dropped below threshold

Result: Fully automated daily performance reports.

🔹 4. Scheduled Email Reports from Firestore Data

Problem: Clients wanted weekly summaries of their app usage.

Our Solution:

• Cron function runs every Sunday
• Pulls KPIs from Firestore
• Generates HTML email
• Sends via SendGrid/Mailgun/SMTP

Tech: Node.js + Firestore + Firebase Scheduler + SendGrid API

📧 Sent ~200 weekly reports without human input.

🔹 5. Queue-Based Video Processor

Problem: Client needed to process user-uploaded videos (resize, compress, tag).

Our Solution:

• User uploads to Firebase Storage
• Cloud Function triggers job into Cloud Tasks
• Worker container (Cloud Run) handles processing
• Updates DB and notifies user via email

Tech Stack: Firebase Storage + Cloud Tasks + Cloud Run + FFmpeg + Nodemailer

🎞️ Reduced video handling time by 70%, added retry and failover support.

🧠 Core Automation Patterns We Use

🛠️ Our Automation Tech Toolbox

We work across multiple stacks:

• Languages: Node.js, Python, TypeScript, Dart
• Infra: GCP (Cloud Run, Tasks, Pub/Sub), Firebase, Supabase, AWS
• Tools: Zapier (for MVPs), Pipedream, n8n, Make.com
• Custom APIs: For tools like Jira, Notion, Figma, Meta, LinkedIn
• Data Stores: Firestore, Supabase, PostgreSQL, MongoDB

💬 What Clients Say

> "Our team used to spend half a day preparing reports. Now it happens in the background, like magic."

> -- Operations Lead, Fintech SaaS

> "They built us a Slack bot that replaced 80% of our PM meeting overhead. Game changer."

> -- Founder, B2B SaaS

📞 Want to Automate Your Workflows?

We help startups, product teams, and enterprises:

• ✅Identify manual bottlenecks
• ✅Replace them with real-time automations
• ✅Save hours of ops time weekly
• ✅Build systems that *scale without dev burnout*