Feature

AI Project Match & Deduplication

AI-Assisted Duplicate Detection for Construction Sales

Baucore uses AI to search for matching construction projects before a new project is created, comparing location, description, and participants.

Baucore AI Project Match result for a student housing scheme with the AI explanation of why the projects match

The Problem

In construction and building product sales, project information flows in from multiple channels: external data providers, emails, forwarded threads, and internal updates. Without duplicate prevention, teams create the same project multiple times, each with partial or conflicting information. Reporting, follow-ups, and accountability break down.

Multiple project records for the same job
Duplicates missed when each source names the same project differently
Conflicting details across duplicate entries
Lost context and duplicated work
Unreliable reporting and pipeline visibility
Confusion about ownership and next steps
Teams lose time, miss follow-ups, work with poor data, and trust the system less.

THE SOLUTION

Before any new project record is created, Baucore searches for possible matches in two passes. Rule-based matching compares project name, geolocation radius, and participant overlap. AI Project Match then reads the project's location, description, and participants to find records that exact rules would miss. Both result sets appear together on the New Project screen, ranked by score, and every AI match comes with a plain-language explanation of why the projects look like the same job.

Core Capabilities

AI Project Match

AI reads the project's location, description, and participants to surface possible matches that name and radius comparison miss.

Explained match reasoning

Every AI match states why it was flagged (shared city, same building use, aligning descriptions), so the team can accept or dismiss it with confidence.

Matching before record creation

Both checks run on the New Project screen, before a duplicate ever reaches the database.

Ranked results with scores

Baucore scores and ranks matches so the team sees the strongest candidates first.

Duplicate detection across sources

Identifies duplicates when project information arrives via email, external data providers, or internal updates.

Link instead of duplicate

Assign incoming information to the existing project so context stays unified in a single record.

HOW IT WORKS

1

New project information enters Baucore from email, external project data, or manual entry

2

Rule-based matching compares project name, geolocation radius, and participant overlap

3

AI Project Match analyses the location, description, and participants to find further candidates

4

Matches are ranked by score and shown with an explanation of why each one was flagged

5

The team links the record to an existing project or confirms it is new

The Benefits

Clean and reliable project database
Catches duplicates that differ in wording as well as address
Faster decisions, since every match explains itself
Fewer missed follow-ups caused by split records
Consistent visibility across teams and workflows
More accurate reporting and forecasting inputs

One project, one record, with less rework and confusion.

Who This Is For

Building product manufacturers
Lighting, HVAC, electrical, and architectural product rep agencies

Valuable for teams aggregating project data from multiple sources and inbox-based communication.

Frequently Asked Questions