AI Exploration
Sourcing in dialogue: describe your thesis in plain language and the AI finds matching targets across multiple sources.
Why Keyword Search Fails
Keywords, Not Thesis
Filter forms force your investment thesis into a few keywords.
Source Hopping
Relevant targets are scattered across databases, newsletters, and banker pitches.
Black-Box Results
Tools return lists with no rationale for why a target fits.
How AI Exploration Works
In dialogue, transparent, reviewable.
- 1
Describe the Thesis
You phrase your thesis in plain language, no filter setup.
- 2
AI Searches in Parallel
The AI scans multiple sources and proposes matching targets with rationale.
- 3
Review and Adopt
Every suggestion can be reviewed or discarded; matches move into your pipeline.
“DACH B2B SaaS, EUR 5–25M ARR, asset-light, founder-owned.”
Your Thesis Stays Confidential
Your queries and thesis data are anonymized before any AI processing, EU-hosted, Swiss company.
Instead of a Filter Database
An AI that understands your thesis, instead of a filter form that only knows keywords.
Frequently Asked Questions
About AI exploration.
How is this different from keyword search?
You describe your thesis in plain language; the AI translates it into criteria and searches across multiple sources, not just keywords.
Are the suggestions traceable?
Yes. Every suggestion comes with rationale and source and can be reviewed or discarded.
Do matches land in the pipeline?
Yes. Confirmed targets move straight into your pipeline and workflow.
Walk Through a Feature Live
See KamiSource against a real mandate setup. 30 minutes is enough.