Why Startup Scouting and Evaluation stopped keeping pace
In 2025, global venture funding hit $425 billion. AI companies captured half of all venture dollars. By Q3 2025, AI accounted for 63% of all deal value over the previous twelve months. No other technology wave has come close.
While the money grew, the number of deals shrank. Deal count dropped to its lowest level since 2016. More capital is flowing into fewer companies. Those companies are bigger, harder to classify, and span more industries than ever. A company building AI for hospital operations is simultaneously an AI company, a health tech company, an enterprise software company, and a workflow company. Which box you put it in changes everything: which companies it gets compared to, which scorecard it gets judged on, and whether it looks like a winner or a write-off.
Most tools to find and evaluate startups were built for a simpler market. That market is gone, because:
You cannot find what you are looking for
Often, scouting still starts with a keyword search. You type in a sector, a stage, a geography, and you get a list. The list contains startups that are dead, startups in the wrong category, and startups that raised years ago. The company that actually fits what you need used different words to describe itself and never showed up.
The tags underneath most databases are built on classification systems updated once every five years and correctly applied only about half the time.
Meanwhile, a 2026 survey of 200 founders found that 81% had changed direction from their original idea at least once. Every time a company changes, the description changes. The tag stays the same.
Slack started as a gaming studio. Shopify started as a snowboard shop. Both were labelled as something they were about to stop being. If you searched for what they became, you would never have found them at the moment it mattered.
You are scoring everything the same way
When a startup makes the shortlist, it gets scored. In most organizations, this means one scorecard. That scorecard almost always assumes the company is a software business: high margins, fast revenue, short payback periods.
But not every startup is a software company. A defense company, a climate tech company, a biotech company, a robotics company, a hardware company: they all run on different economics, different timelines, and completely different definitions of progress. Each has its own set of metrics that matter. Score any of them on a software scorecard and they will look broken.
But they are not broken, the scorecard is wrong for the company in front of you. The person doing the evaluation is not making a mistake. The tool gives everyone the same scorecard. When there is not enough time to build a custom one, the scorecard makes the decision.
Nobody checks the numbers
The pitch deck says 50,000 active users. The company’s own website says 30,000 registered accounts. The patent section claims twelve patents across five countries. The public registry shows three applications in one country. The market size slide cites a $47 billion figure from a 2023 report. The next startup in the pipeline cites the same report, the same number.
Investors receive thousands of decks a year and spend less than four minutes on each one. At that pace, you can form an impression. You cannot check a single claim. But the score that comes out looks just as confident as if every number had been verified.
When a deal goes wrong, the information was almost always there. The registry was public, the website was live, nothing was hidden: It just was not part of the process.
Kuanta evaluates startups across 19 industry verticals, each with its own scorecard, its own warning signs, and its own definition of what good looks like. We scout across 3.7 million validated profiles using semantic matching that finds companies by what they do, not by what label they carry. We built it this way because the old way stopped working. Curious how we can revolutionize your deal flow?
Book a demo with us today.
