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Scouting Platform

A custom scouting platform built for Vejle Boldklub, delivered in 5 weeks with AI embedded at the core. It replaces a heavy spreadsheet with structure, automation and intelligent data analysis.

Scouting Platform
5 weeks From idea to launch with AI-assisted coding
4 AI features built into the core
Auto Club contact emails on scout assignment
0 Manual entry of DBU data
The challenge

Before the platform, Vejle Boldklub kept all their scouting data in one Google Sheet. Scouts didn't have access to write into the sheet themselves. They observed matches, took notes and passed their reports on to admin, who then spent many hours each week typing every report into the spreadsheet by hand. Matches on DBU's website had to be found and copied over manually. Call-up PDFs from DBU were read through and entered the same way. And when a scout was sent out to a partner club, the communication was done over SMS or email, written from scratch every time. Most of the manual work landed on admin, and it no longer scaled.

The solution

We built a custom web platform with AI at the core, delivered in 5 weeks. By using AI-assisted coding as part of our own development process, we delivered a system that would normally take months. AI isn't an add-on in the platform - it's embedded where it creates real value: report analysis, document parsing, player matching and DBU match import. On top of that, we automated the club communication so partner clubs are notified when a VB scout is on the way, once admin has approved the email.

How it works

The whole project is an example of how alpha.ai builds systems faster and smarter than traditional vendors. By using AI as an active part of our own development process - coding, refactoring and testing - we delivered a fully custom platform in 5 weeks. It isn't a template system, but built specifically for Vejle Boldklub's scouting workflow.

AI is embedded where it creates real value. When multiple scouts have reported on the same player, AI summarizes the assessments into one unified view and extracts the keywords that recur across reports. The head scout gets the essence without reading everything. AI never changes ratings or player data on its own; it acts as an analysis tool, not a decision-maker.

The DBU integration removed one of the biggest manual bottlenecks. Match overviews and individual matches are pulled directly from DBU's website and turned into scouting tasks in the system, ready to be distributed to the scouts in a structured way so matches and data no longer slip through the cracks. Call-up PDFs from DBU are uploaded and parsed automatically: AI reads the document, extracts player data, matches it against existing profiles in the database, and creates new players where there's no match.

One of the more elegant details in the system is the club communication. When Vejle sends a scout to one of their partner clubs, admin has pre-created a contact person at the club. The moment the scout is assigned the match - either by admin or by picking it up themselves - the system automatically prepares an email to the contact person with match and date. The email is only sent once admin has approved it. It brings structure and speed to the communication while keeping admin in control of what goes out.

Underneath it all sits a solid approval flow on the reports. Scouts write following a fixed schema with numeric rating, position and preferred foot, but nothing affects a player's profile before admin has approved the report. That gives Vejle control over data quality and keeps the database consistent, unlike the old spreadsheet where scouts couldn't write into it themselves and admin had to assemble the whole picture manually.

Features

What the system does

AI report analysis

AI summarizes multiple reports on the same player into one unified view and extracts recurring keywords from scout comments. The head scout gets the essence without reading everything.

AI parsing of DBU documents

DBU call-up PDFs are uploaded and parsed automatically by AI. The system matches players against existing profiles or creates new ones, with no manual entry.

DBU match import via AI

Match overviews and individual matches are pulled directly from DBU's website and turned into scouting tasks, ready to distribute to the scouts.

Automatic club contact with approval

When a scout is assigned a match, an email to the partner club's contact person is prepared with match, date and players. Admin approves it before it's sent.

Structured reports with approval flow

Standardized report schema with numeric rating, position and preferred foot. Every report goes through admin approval before it affects a player's profile.

Searchable player database

It replaces the spreadsheet with a central database. Filter by age group, club, position and rating, with full report history, average rating and AI keywords per player.

The change

Before vs. after

Before the platform

  • All scouting data kept in one Google Sheet
  • Scouts handed reports to admin, who spent many hours each week on manual entry
  • Matches were found and copied manually from DBU's website
  • DBU PDFs were read and entered by hand
  • Club communication was written from scratch every time
  • No approval flow and no unified quality control of data

With the platform

  • Custom platform with AI built into the core
  • Scouts now write reports directly in a fixed schema themselves
  • DBU matches are imported automatically and distributed to scouts
  • AI parses DBU PDFs and matches players automatically
  • Club emails are prepared automatically, admin approves before sending
  • Every report goes through admin approval before it counts
The process

From idea to launch

1
Step 1

Discovery

We met with Vejle Boldklub, listened to how scouting worked today, and mapped out goals, pain points and wishes for the new system.

2
Step 2

Requirements and quote

Based on discovery, we wrote a requirements specification describing the full solution in detail and paired it with a commercial proposal.

3
Step 3

Roadmap and tasks

Once the requirements were approved, we built a roadmap for the project and broke it down into concrete tasks.

4
Step 4

Production

The actual development of the platform. Feature by feature, with AI-assisted coding as part of the process, so we could keep the pace without compromising quality.

5
Step 5

Internal testing and refinement

Once the system was built, we ran an internal testing phase where we adjusted details and fixed smaller issues before it went out to the client.

6
Step 6

Client trial run

Vejle Boldklub got the system in their hands and trial-ran it in their real day-to-day work. We gathered feedback and adjusted along the way.

7
Step 7

Handover

With the system stable and the client ready, we handed the platform over to Vejle Boldklub as a finished solution, ready for daily operation.

Results

The heavy spreadsheet has been replaced by one structured system. Scouts now write their reports directly into the platform following a fixed schema, AI summarizes across reports, and DBU data flows in automatically. Admin no longer spends hours each week on manual data entry. The club owns the platform 100% and got the entire solution delivered in 5 weeks thanks to alpha.ai's AI-driven development process.

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