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AI speeds up launches for Singapore cloud firm

Launch cycles cut from weeks to days

Cloud Services / MSPSingaporeAI Coding Agent, AI Support Chatbot, Cloudflare 24/7 Monitoring

A Singapore-based cloud services company engaged AWM to modernize how it ships customer-facing experiences. Within days the AWM team embedded our Codex AI Coding Agent, refreshed the public website, and stood up proactive automations that keep high-value enterprise clients informed.

Client Snapshot

  • Industry: Managed cloud and network services for regulated enterprises
  • Engagement: White-labeled pod combining AI engineering, n8n ops, and observability
  • Core Goals: Launch a new website, automate support, and maintain Cloudflare SLAs

The Challenge

  • Rebuild the flagship marketing site without exposing the client brand pre-announcement
  • Provide real-time answers for enterprise customers without scaling human support seats
  • Monitor Cloudflare incidents for a major strategic customer and notify support instantly

How AWM Helped

We mobilized a small automation strike team to tackle the roadmap in parallel tracks:

  • Codex fueled delivery - The AI Coding Agent paired with AWM engineers to rebuild the website experience, enabling full-content rollout in days instead of multi-week sprints.
  • n8n customer support copilot - We wired an AI chatbot that understands playbooks, surfaces automation runbooks, and hands off to live agents with complete case context.
  • Cloudflare status monitor - Lightweight service polls the Cloudflare incidents API and pushes alerts to technical support, reducing time-to-awareness for regional outages.

Architecture Highlights

  • Static Next.js site hosted on Vercel with dark-mode default and staged content collections
  • Serverless API hooks to n8n flows for human-in-the-loop escalation
  • Scheduled monitoring job caching Cloudflare responses and broadcasting alerts via Telegram to maintain SLA

Cloudflare Monitoring Workflow

The diagram below outlines how the monitoring job polls for incidents, deduplicates events, and notifies the Singapore support squad with enriched context and SLA timers.

Sequence diagram describing the Cloudflare monitoring automation
Workflow: poll → filter → contextualize → alert + escalate.

Impact

  • Public site refresh shipped in 4 business days (previous cadence averaged 3+ weeks)
  • AI chatbot deflects ~62% of recurring support tickets with human-quality responses
  • Support team now receives Cloudflare outage pings within 90 seconds of an incident
  • Confidential branding preserved thanks to white-label collaboration practices

Next Steps

With the foundation live, we are layering FinOps reporting into the same automation backbone and adding runbook-driven remediation for Cloudflare service degradations.

Need to move just as fast?

Talk to AWM about pairing Codex with our automation pods under your own brand.