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AI Workflow Automation

Replace repetitive operations with reliable, monitored automations across your existing stack.

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Turn scattered docs, tickets, and SOPs into a precise, queryable knowledge layer with citations.

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Custom operational dashboards and internal platforms that surface AI outputs, monitor workflows, and put data where teams need it.

Ways to Start
AI Systems Audit

Find where AI can create practical value before building the wrong thing.

AI Architecture & Discovery Sprint

De-risk your AI product build with a clear technical roadmap, architectural blueprint, and interactive prototype.

Workflow Automation Sprint

Turn one repetitive workflow into a reliable automated system.

AI Agent Build Sprint

Build a custom AI agent that performs a defined business task with guardrails.

RAG Knowledge System Sprint

Turn scattered knowledge into a reliable AI assistant your team can trust.

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All ServicesAI Workflow AutomationCustom AI AgentsRAG & Knowledge SystemsAI SaaS Product EngineeringAI Chatbots & AssistantsDashboards & Internal Tools
AI SprintsAI Systems AuditAI Architecture & Discovery SprintWorkflow Automation SprintAI Agent Build SprintRAG Knowledge System Sprint
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All case studies
AI Automation

Google Reviews Automation

An AI-powered automation system built to centralize Google reviews, detect employee mentions, identify photo reviews, and simplify monthly bonus reporting for a multi-location service business.

  • Make.com
  • Gemini AI
  • Google Sheets
  • DataForSEO
  • Google Reviews
+1 more
01
Business type

Multi-location service business

02
Core problem

Manual review tracking and bonus calculation across several locations

03
Main outcome

Centralized reporting with AI-assisted employee detection

Business impact

Replaced manual review checking with a repeatable reporting workflow, giving the team faster visibility into store-level review activity and bonus reporting without adding headcount.

The challenge

The business friction

The client needed a reliable way to track new Google reviews across multiple locations, identify whether employees were mentioned, detect photo reviews, and calculate monthly bonus eligibility. The process was manual, time-consuming, and difficult to scale as more locations were added.

The solution

The system response

MASK AI built an automated review tracking system that collected review data, processed it through AI extraction, identified employee mentions and photo status, and organized the results into a centralized reporting layer for monthly bonus review.

Capability map

What the system covers

Built around the operational jobs that matter: intake, product experience, workflow control, visibility, and follow-through.

01

Multi-location review tracking

02

AI employee mention detection

03

Photo review identification

04

Monthly bonus eligibility logic

05

Centralized Google Sheets reporting

06

Automated review checks

07

Manual review flags for unclear cases

Operating path

How the system flows

Reviews move from location sources into AI extraction, reporting, and bonus review.

Review intelligence pipeline

Reviews move from location sources into AI extraction, reporting, and bonus review.

06 stages
01
Google Reviews
02
DataForSEO
03
Make.com
04
Gemini AI
05
Google Sheets
06
Monthly Bonus Report
Technology

Stack and architecture

The engagement combined product interface work, workflow logic, and implementation tooling around the operational needs of the project.

  • Make.com
  • Gemini AI
  • Google Sheets
  • DataForSEO
  • Google Reviews
  • Webhooks
Outcome

What changed

The system reduced manual review tracking, improved bonus visibility, centralized reporting across locations, and created a scalable process for future expansion.

Review visibility
Bonus reporting
Less manual checking
Let's talk

Need a similar system?

Let's build it.

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MASK AIMASKAI

Engineering-grade AI systems, automation workflows, agents, and software platforms for serious operators.

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  • +92 309 7385611
  • Islamabad, Pakistan
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