🎉 Supa - AI Platform for Event Management (UK)

Workflow-driven system for event process management and automation

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📌 Context and Challenge

The Supa project addresses a classic problem in the event industry:

• communication with suppliers is manual (email, messengers)
• contractor selection is chaotic
• date and price negotiation is a lengthy process
• information is fragmented (spreadsheets, emails, calendars)

Engineering task:

to consolidate all event organization processes into a single manageable system with AI automation

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🎯 System Goal

• automate interaction between participants
• accelerate supplier selection and terms negotiation
• reduce manual correspondence
• make the process transparent, trackable, and reproducible

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🧠 Architectural Approach

Core Principle:

AI-first + workflow orchestration + multi-tenant platform

The system is built as:

• a set of domain services
• a unified AI assistant layer
• an event-driven interaction model

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🧩 Key Modules

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👤 1. User Accounts (Multi-role Accounts)

Support for various roles:

• event organizers
• suppliers (catering, venues, logistics)
• managers

Functionality:

• role-based access
• data isolation (multi-tenant)
• custom scenarios per role

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✉️ 2. Communication Module (Messaging Engine)

Internal messaging system between accounts:

• organizer ↔ supplier dialogues
• communication history storage
• message status

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🤖 AI Email Generation

Key feature:

• email generation based on request templates:

• date inquiry

• price inquiry

• service clarification

• adaptation to supplier context

Technically:

• LLM + prompt templates
• context = dialogue history + supplier profile

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🧠 3. Manager AI Assistant (Core AI Layer)

Central component of the system.

Functions:

📅 Date Availability Check

• supplier calendar analysis
• consideration of business rules (buffer, load)

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📌 Booking via Chat

• user types: "book for June 15th"

• system:

• validates slot

• creates event

• records booking

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🍽 Menu and Price Selection

• parsing supplier documentation

• extracting:

• menu

• prices

• recommendations based on budget

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🔍 Supplier Selection

• search by database

• filtering:

• price

• service type

• availability

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⚙️ How it's Implemented

AI Assistant = orchestration layer:

• intent detection
• request routing
• calling domain services

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📬 4. RFQ (Request for Quotation) Engine

Automation of quotation requests:

1. request is formed
2. sent to suppliers
3. responses are aggregated
4. best option is selected

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📦 5. Supplier Booking

• recording the selected contractor
• date blocking
• link to event

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📅 6. Event Calendar

Functionality:

• create / edit events
• display participants
• synchronization with bookings

Peculiarity:

calendar = source of truth for the entire system

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🚚 7. Logistics Calculation

• delivery cost calculation
• distance consideration
• integration with supplier rates

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🏗 System Architecture

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🧱 Microservice Structure

• Account Service
• Messaging Service
• AI Service
• Supplier Service
• Booking Service
• Calendar Service
• Pricing/Logistics Service

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🔄 Event-Driven Model

• events:

• message_sent

• supplier_selected

• booking_created

• event_updated

Used for:

• service synchronization
• reactive logic

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🧠 AI Layer

Separate service:

• LLM orchestration
• prompt management
• tool calling

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⚙️ Process Orchestration

Approach analogous to fintech:

each event = workflow

Example:

Create Event →
Select Suppliers →
Request Quotes →
Compare →
Book →
Manage Event →
Close