Equip Mining Parts & Components

Context

Equip Mining Parts & Components is a founder-led mining equipment parts venture focused on sourcing OEM-quality parts through China supply channels for Australian resale. The business requires disciplined product data, supplier response handling, customer RFQ workflows and part-number integrity from the beginning rather than after operations become messy.

Problem

Mining parts knowledge is often fragmented across supplier emails, spreadsheets, part-number variants, personal memory and informal process. That creates rework, slows RFQ response, weakens customer confidence and increases the need for manual administration.

Benjamin’s Role

Benjamin is founder, business builder, technology architect and AI-assisted ERP product owner. He is shaping the commercial model and the operating system together.

What Benjamin Built Or Changed

• Odoo ERP foundations for supplier RFQs, customer RFQs, procurement and product data.
• Product and part-number integrity for OEM, replacement, remanufactured, superseded and alternative numbers.
• Data-cleansing workflows and enrichment thinking using ZoomInfo-style data and ABR-assisted Australian company matching.
• Target-account management, supplier and customer portal concepts, freight logic and procurement workflow.
• Codex-assisted module development, troubleshooting and documentation.

Stakeholders

Founders, suppliers, target customers, freight providers, future administrative users and future account-management users.

Delivery Approach

Benjamin is using a lean builder approach: capture business rules, encode repeatable process in Odoo, validate edge cases through live records, use AI to accelerate coding and documentation, and keep human review over commercial and data-quality decisions.

Outcomes

The venture demonstrates how ambiguous specialist business knowledge can be turned into a repeatable operating platform. It also shows how AI-assisted development can reduce reliance on large offshore administrative teams by moving process and decision support into the system.

What It Demonstrates

Founder judgement, ERP architecture, practical AI use, hands-on implementation and the ability to convert messy commercial knowledge into governed workflow.

Source Or Evidence Note

The naming and detailed commercial framing are user-supplied and should be confirmed before final publication. Local development history provides implementation evidence, but public detail should remain commercially reviewed.