AI Match M&A Project
Client
Small enterprise
Sector
Business Consulting
Revenue
€ Data not available
Client
Small enterprise
Sector
Business Consulting
Revenue
€ Data not available
From challenge...
Automating M&A scouting without losing precision and control.
In the acquisitions market, information on target companies is often scattered across heterogeneous sources, databases, online content and qualitative analyses, making deal sourcing slow, costly and difficult to scale. The challenge was to build a process capable of identifying and selecting target companies, reducing scouting time and costs, integrating financial, qualitative and sector-specific data, and generating personalized, verifiable shortlists for funds, acquisition teams and advisors.
...to result
AI MatchM&A turns scouting into a faster, more structured and measurable process.
The platform integrates heterogeneous data sources, enriches company profiles and supports target selection through automated classification, intelligent matching and Human in the Loop supervision. The Proof of Concept validated the full pipeline, from scraping to final matching, on a dataset of over 100 companies: LLM-generated descriptions received over 90% positive validations, while automated classification was confirmed by reviewers in over 80% of cases.
Expected benefits include a 50% reduction in scouting time, a 30% increase in matching effectiveness, and faster, traceable shortlists that can be continuously improved over time.
From challenge...
Automating M&A scouting without losing precision and control.
In the acquisitions market, information on target companies is often scattered across heterogeneous sources, databases, online content and qualitative analyses, making deal sourcing slow, costly and difficult to scale. The challenge was to build a process capable of identifying and selecting target companies, reducing scouting time and costs, integrating financial, qualitative and sector-specific data, and generating personalized, verifiable shortlists for funds, acquisition teams and advisors.
....to result
AI MatchM&A turns scouting into a faster, more structured and measurable process.
The platform integrates heterogeneous data sources, enriches company profiles and supports target selection through automated classification, intelligent matching and Human in the Loop supervision. The Proof of Concept validated the full pipeline, from scraping to final matching, on a dataset of over 100 companies: LLM-generated descriptions received over 90% positive validations, while automated classification was confirmed by reviewers in over 80% of cases.
Expected benefits include a 50% reduction in scouting time, a 30% increase in matching effectiveness, and faster, traceable shortlists that can be continuously improved over time.
The solution
We developed an AI platform for scouting in the acquisitions market, designed to transform a manual and fragmented process into a faster, structured and measurable workflow. The system integrates heterogeneous data sources, enriches company profiles and supports target selection through automated classification, intelligent matching and Human in the Loop supervision. Users define selection criteria, the platform completes the information on target companies and proposes prioritized shortlists with affinity scores.
What we implemented:
- Creation and modification of selection criteria, with filters and sorting
- Company profile enrichment from structured and unstructured sources
- Company descriptions, insights and summaries generated with LLMs
- Automated target classification with Human in the Loop supervision
- Market analysis reports on size, players, trends and clusters
- Matching between targets and buyers with a 0–100 score
- CSV or PDF export for internal sharing and stakeholder reporting
Technology stack