The problem
Basic database filters are rarely enough. Even after filtering by industry, size or location, sales teams still face long lists that require manual qualification.
Product · Lead qualification
CompanyScorer
CompanyScorer evaluates large company lists against a custom target profile. Instead of manually reviewing hundreds or thousands of records, AI qualifies the most promising companies first.
The solution
CompanyScorer combines structured company data, web signals and LLM-based evaluation to rank companies against custom qualification profiles.
The outcome
Sales teams can start from a ranked shortlist instead of a raw longlist, which makes outreach faster and more focused.
Example use case
From 2000 companies to a realistic outreach list
A strong example is outbound sales where a HoReCa distributor already has a large initial list from traditional filters but still needs to determine which companies actually fit the target profile.
- Existing lists from NorthData-like sources can be imported as the starting point.
- A target profile defines which signals matter for fit, exclusion or prioritization.
- LLMs and crawling automatically qualify companies against those criteria.
- Customer feedback continuously sharpens the profile and improves future scoring.
- n8n or Make integrations can send qualified results straight into outreach flows.
Practical impact
This does not replace sales. It removes the most repetitive pre-work.
The result is not a generic black-box score. It is a qualification process aligned with your actual customer profile and refined with ongoing feedback.