Case study: Event equipment supplier

Context and goal

Client

Event equipment supplier (B2B and B2C)

The client runs a dynamic business with inventory rentals, event organization, and team coordination.A modern, centralized system is needed that optimizes processes, reduces errors, and provides quick access to real-time information.

Goal

To create a web-based platform that digitizes event, inventory, and customer management, automates operational processes, improves coordination between teams, and uses AI for demand forecasting, pricing, and schedule optimization.

Challenges (before)

Limited visibility on rentals, returns, and events

There is no centralized platform to visualize the operational status of the business.

Разпокъсана информация за инвентара

There is no full control over statuses, availability, and usage history.

Risks of late returns and missing key items

Tracking is done manually and leads to operational errors.

Unclear customer engagement and interaction history

Customer data and contracts are not centralized.

Difficulties in preparing quotes and tracking payments

Calculations and documentation are manual and slow.

Lack of analytical tools for financial control and workload

The management team does not have access to quick reports and detailed statistics.

Central dashboard with key indicators

Visualizes active rentals, upcoming events, late returns, and monthly income.

Interactive calendar of events

Present reservations with color codes and allows for quick edits and new requests.

Inventory module with full traceability

Track quantities, statuses, usage history and automatic notifications for low stock or delays.

Client module with full interaction history

Panel with complete information about rentals, contacts, payments and statuses.

Generating and managing offers

Automatic price calculation, status tracking and PDF export.

AI inventory workload prediction

Determines which items will be searched for in specific periods.

AI dynamic pricing

Offers optimal prices according to demand, availability and seasonality.

AI assistant for schedule and team management

Detects conflicts, suggests reassignments, and distributes tasks based on occupancy and location.

Solution:

Implementation

Duration

12 weeks (analysis → build → integrations → AI functionalities)

Scope

Inventory management, reservations, customers, quotes, scheduling, financial reports;integration with external systems and mobile devices

KPI

Defined and monitored in real-time (see "Achieved Results")

Achieved results (5 months after implementation)

+34%
Higher accuracy in resource management
AI forecasts enabled more precise planning of inventory workload.

-41%
Less operational time for order processing
Automation has significantly reduced the time for creating, approving, and distributing requests.

+27%
Higher team efficiency
The AI assistant optimizes tasks based on availability and location.

-29%
Fewer missed or conflicting reservations
The smart calendar eliminates common errors and overlaps.

+16%
Revenue growth YoY
Optimal pricing and better control over processes increased annual revenues.

+22%
Increased customer satisfaction
Faster responses, accurate quotes and better request management.

-18%
Lower inventory replacement and service costs
Timely monitoring for workload and repeated use reduced depreciation.

What we learned / next steps

Automation is critical for dynamic and fast-paced processes

The system minimizes errors and speeds up service.

AI increases predictability and optimizes resource planning

It gives a clear picture of future workload and availability.

Next steps

Expanding AI for recommendations in complex events and integrating a module for personalized packages for customers.

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