Discoperi began as an automotive data and AI company — building intelligence systems that could see, analyse, and act on complex signal environments in real time. We are applying that same infrastructure to the world of mergers and acquisitions: a market where signal quality is uneven, data is expensive, and the people who most need visibility are the ones who can least afford Bloomberg Terminal seats.
The M&A information market has a structural problem: the best data costs $30,000+ per year per seat, which means it's available to bulge-bracket banks and large PE funds — and essentially no one else. Corporate development professionals at mid-size companies, boutique bankers, M&A lawyers, and independent analysts operate with fundamentally worse information than their larger-firm counterparts.
We built the M&A Intelligence Engine to close that gap. Using AI extraction, multi-source cross-referencing, and a fully automated publishing pipeline, we surface verified closed deals — including lower and mid-market PE transactions that the major data providers don't cover — at a price that a single analyst can justify to their manager.
Previously led AI product at Discoperi automotive. Building the M&A intelligence layer for the next decade of deal professionals.
LinkedIn →We publish verified deals, not rumours. A 2-hour delay in exchange for cross-referenced accuracy is the right trade-off for a professional audience.
Every published deal includes its sources, confidence score, and methodology. You should always know exactly how we know what we know.
The Bloomberg Terminal costs $32,000/year. That shouldn't be the only option. Good deal intelligence should be accessible to anyone in the ecosystem.
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