Rifki Rosada | Automation Systems

AI Content Research & Script Automation

Converted manual financial/content research into an AI-assisted script pipeline for topic discovery, references, Google Docs drafts, and Sheets approval tracking.

AI Automation Engineer Completed May 2026 Remote contract delivery
  • Problem

    Before delivery, each script cycle required manual scanning for current topics, reference validation, source summarization, short-form script drafting, Doc creation, and review-status tracking.

  • My scope

    Mapped the end-to-end content operation: topic discovery, reference collection, summary generation, script drafting, Docs export, and Sheets-based status review.

  • Result

    Converted manual content research into a repeatable AI-assisted script pipeline with Docs output and Sheets approval tracking.

Problem

Before delivery, each script cycle required manual scanning for current topics, reference validation, source summarization, short-form script drafting, Doc creation, and review-status tracking.

Constraints

  • The workflow had to support current-topic research while keeping private prompts, references, and client documents out of the public case study
  • References and summaries needed enough traceability for human review before scripts moved forward
  • The client needed the system inside Google Workspace, not a separate product the team would have to learn

System workflow

  • Mapped the end-to-end content operation: topic discovery, reference collection, summary generation, script drafting, Docs export, and Sheets-based status review.
  • Built an AI-assisted research pipeline that turns selected topics into summarized source notes and short-form script drafts.
  • Connected generated outputs to Google Docs for draft review and Google Sheets for approval/status tracking.
  • Added workflow QA around references, generated sections, and handoff states so the system could be reused safely across content batches.

Result

  • Replaced a manual research-and-drafting chain with a repeatable pipeline covering topic discovery, source collection, source summaries, script drafts, Docs output, and Sheets tracking.
  • Reduced research and drafting friction by keeping references, drafts, and approval state in one Google Workspace workflow.
  • Created a reusable delivery pattern for content automation: AI generation where it saves time, human review where accuracy matters.
  • Client review: "Exceeded expectations and delivered fast."

Client proof

Exceeded expectations and delivered fast.

IZZY — AI content automation client
Translated client review

Tech stack

  • OpenAI
  • Google Apps Script
  • Google Docs
  • Google Sheets
  • Google Workspace
  • Research Automation
  • Workflow QA

Related delivery proof across internal tools, automation, Android + AI, and supporting product systems.

Automation Systems

Client delivery

Inbound Order & Lead Ops Automation

Automation Engineer2-week delivery sprint

Eliminated an estimated 60–80 hours/month of manual data entry across multi-branch operations. Booking + reporting now flow automatically into a single source of truth.

  • Problem

    Inbound orders, bookings, and chat updates were copied manually into spreadsheets across multiple branches, producing inconsistent records, delayed follow-up, and zero operational visibility for management.

  • My scope

    Implemented web-order-to-sheet automation with validation and normalization.

  • Result

    Eliminated an estimated 60–80 hours/month of manual data entry across multi-branch operations. Booking + reporting now flow automatically into a single source of truth.

  • n8n
  • Google Apps Script
  • Google Sheets
Read case study

Automation Systems

Client delivery

SP2DK & LHP2DK WhatsApp Reminder System

Google Workspace Automation EngineerCompleted Jun 2026

Turned deadline monitoring into a structured reminder workflow with H-7/H-3/H-1/Overdue buckets and WhatsApp-ready follow-up.

  • Problem

    Before delivery, SP2DK/LHP2DK monitoring depended on manual deadline checks, scattered status review, and follow-up visibility that was easy to miss as records moved across owners and sections.

  • My scope

    Mapped the follow-up operation around document type, due date, status, responsible staff/section, and reminder bucket.

  • Result

    Turned deadline monitoring into a structured reminder workflow with H-7/H-3/H-1/Overdue buckets and WhatsApp-ready follow-up.

  • Google Apps Script
  • Google Sheets
  • Apps Script Web App
Read case study

Client Systems

Client delivery

Enterprise CRM - Sales Pipeline & Performance System

Lead Full-Stack Engineer6-week delivery sprint

Cut the weekly pipeline review cycle from ~2 days of spreadsheet reconciliation to ~15 minutes — single source of truth across sales, ops, and management.

  • Problem

    Pipeline updates and performance reporting were split across 3 separate spreadsheets, making weekly reviews take days and ownership hard to trust.

  • My scope

    Mapped sales stages, reporting rules, and operator roles before touching schema or UI.

  • Result

    Cut the weekly pipeline review cycle from ~2 days of spreadsheet reconciliation to ~15 minutes — single source of truth across sales, ops, and management.

  • Laravel
  • Next.js
  • PostgreSQL
Read case study

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