Bet365 Sports Automation Platform
Real-time sports operations platform — Telegram signal ingestion, Bet365 API automation, and audit-ready execution.
01 / Industry
Sports Technology
02 / Features
8
03 / Stack
6
04 / Delivery
AI-native
What we delivered on this build
Services
- Backend Development
- API Integration
- Bot Development
- AI / ML Integration
Technology
- Java 17
- Spring Boot
- MySQL
- Telegram Bot API
- OpenAI Vision API
- Docker
Project overview from the brief
Original case study content from Ingenious Minds Lab — adapted for this archive.
Spring Boot platform that monitors publisher Telegram channels, parses structured event signals, and executes actions on Bet365 with multi-sport, multi-tenant controls, AI-assisted screenshot parsing, and Google Sheets reporting.
At a glance
- Industry
- Sports Technology
- Capabilities
- 8 features
Challenge & solution how we delivered
01 · Challenge
High-volume concurrent signals, fuzzy team matching, and full request lifecycle traceability across accounts and tenants.
02 · Solution
Configurable filters, onboarding pipelines, concurrency controls, and production observability for sports automation teams.
What stands out in the product
01 · Highlight
30+ Channel Parsers
Dedicated parser per publisher covering plain text, screenshots, and structured payloads across soccer, basketball, tennis, and more.
02 · Highlight
OCR + OpenAI Fallback
Tesseract OCR handles image payloads; OpenAI Vision fills gaps when OCR output is ambiguous, targeting near-complete signal extraction.
03 · Highlight
Onboarding Pipeline
Automated account conditioning runs controlled activity across configurable leagues and market types before accounts go live.
04 · Highlight
Fuzzy Match Engine
Custom team name resolution using cosine similarity and Levenshtein distance with noise filtering for club suffixes and age-group modifiers.
What the product delivers for end users
01 · Feature
Multi-Channel Signal Parsing
Supports 30+ Telegram publisher channels, each with a dedicated parser that normalizes its unique text and attachment formats into a shared signal schema.
02 · Feature
AI-Assisted Image Parsing
Screenshot-based messages run through Tesseract OCR. When confidence is low, an OpenAI Vision API fallback extracts structured event and market fields from the image.
03 · Feature
Multi-Sport Market Resolution
Resolves markets across Soccer, Basketball, Tennis, Volleyball, Handball, and Ice Hockey — including complex segments such as handicaps, totals, corners, and cards.
04 · Feature
Account Onboarding Pipeline
New platform accounts follow a configurable onboarding flow with gradual, low-volume activity on selected leagues before promotion to live signal processing.
05 · Feature
Fuzzy Team Name Matching
A custom engine using Levenshtein distance and cosine similarity maps publisher team labels (including suffixes like FC, U21, Reserves) to official event names with high accuracy.
06 · Feature
Telegram CLI Management
Operators manage customers, accounts, and channel subscriptions through Telegram commands and interactive menus without direct server access.
07 · Feature
Google Sheets Reporting
Completed actions and system events sync to Google Sheets via the Sheets API for customer-facing dashboards and audit trails.
08 · Feature
Concurrent Multi-Account Execution
Per-account and per-session locks with a queue manager let multiple accounts run in parallel without session conflicts or race conditions.
Product in context visual archive
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Response time
Under 1 business day
Confidentiality
NDAs on request
First prototype
Often within a week