Back to Modules
Core Module 01

INTELLIGENT OPERATIONS

AI Automation

Automate repetitive work, connect business tools, and deploy AI workflows that reduce manual operating cost.

This module turns manual operations into monitored AI workflows. It is useful when teams repeat the same research, reporting, content, email, data entry, support, or approval tasks every week.

Best for

Best-fit use cases

Operations teams with recurring manual work

Companies using many disconnected tools

Teams that need measurable time and cost savings

Pricing

Package ranges

These ranges are decision-making references. Final scope and price should be confirmed after discovery.

Workflow Starter

$2,000 - $8,000

One narrow workflow such as email triage, lead routing, report generation, or social scheduling.

1-2 integrations
Simple AI decision logic
Basic logging
Launch handover

Department Automation

$15,000 - $45,000

A connected automation system for one department with multiple workflows and approval points.

4-8 integrations
Private data handling rules
Human review queues
Operational dashboard

Enterprise AI Ops

$50,000 - $100,000+

Secure, multi-team automation with custom orchestration, governance, and deeper system integration.

Custom backend services
Role-based access
Advanced monitoring
Optimization support

Scope

What is delivered

Each module includes planning, architecture, implementation, launch support, and practical handover instead of code alone.

Workflow map and automation opportunity audit

n8n or custom automation flows with AI model calls

Prompt and tool-use logic for the selected workflows

Monitoring, handoff, and failure recovery rules

Documentation and team training for maintaining the automation

Outcomes

Useful business outcomes

Reduce repetitive operating work by up to 60% when the process is stable and measurable.

Connect CRM, email, spreadsheets, databases, chat tools, forms, and internal systems.

Create auditable human approval points for high-risk actions.

Give teams dashboards for workflow health, queue status, and failure handling.

Process

Delivery process

01 / 1-2 weeks

Discovery and analysis

Identify repeated work, risk points, systems, data access, and expected ROI.

02 / 2-4 weeks

Workflow architecture

Design triggers, AI decisions, human approvals, integrations, and failure paths.

03 / 3-6 weeks

Build and testing

Implement automations, test edge cases, and validate output quality with real examples.

04 / 2-3 weeks

Deployment and optimization

Launch with monitoring, train the team, and tune prompts and routing after live use.

Useful information

Notes and technology

n8nOpenAI modelsClaudeGeminiNode.jsPostgreSQLREST APIsWebhooks

Best results come from clear, repeated processes with known inputs and outputs.

For Mongolian clients, flexible payment and local-currency settlement can be discussed.

Final pricing depends on integrations, data sensitivity, urgency, and maintenance needs.

Related modules