Clean watches company changes to catch a narrow buying window

A new factory, an engine supplier and a first demonstration flight told a battery seller something a static contact list could not. Clean connected those events at a prospective aircraft customer and flagged a possible opening for a sales conversation.

The sequence, described in the company's launch announcement, captures its approach to sales data. Clean monitors business changes over time and interprets them in the context of what a customer sells. It wants to tell salespeople and their AI agents why a particular account might need attention now.

In the aircraft example, Clean says it identified the person selecting suppliers, who replied to its customer within 15 minutes. The prospect had already chosen a battery supplier that week but was still willing to talk. That is a useful indication of timing, not a reported contract win.

The startup says it watches more than 1,000 sources, including filings, product specifications, press releases and hiring notices. It first learns about a seller from its website and documents, then assembles relevant events for potential customers and identifies decision-makers.

Watch Clean's original launch video.

Its website illustrates a similar process for manufacturing sales, using signals such as permits, equipment shipments and financing. Those observations are intended to add up to a reason a company might buy a particular product, rather than a generic score saying the company looks active.

Clean says its signals include sources, giving users a way to inspect the evidence behind a recommendation. That matters because a public event and a purchasing decision are not the same thing. A new facility can be relevant to a vendor without proving that a budget is available or a buying process is still open.

The company offers its own application as well as an API and MCP access for tools such as Claude and Codex. It also describes connections to CRM and outreach workflows. Those channels let a salesperson use the information directly or make it available to an agent handling parts of the sales process.

Clean is part of Y Combinator's Fall 2026 batch. Its four founders are Pavan Kumar Naguvanahalli Yashavantha, Tejas Gupta, Pratham Patel and Clarissa Saputra. Their backgrounds span enterprise sales, growth, machine-learning engineering and research. Pavan's public profile includes enterprise sales at Cisco and community-building at Cliqk.

The company reports that customers have generated more than $1 million in revenue using Clean. It also cites improved reply rates and booked meetings. These are company-reported results, without a published controlled comparison showing how much of the outcome came from the product rather than the seller, offer or market.

Clean's wider ambition extends beyond finding prospects. It describes the same changing account record as useful for expansion opportunities and customer risk, giving both people and agents context throughout a commercial relationship. The launch's most tangible evidence, however, concerns identifying and approaching potential buyers.

The battery-supplier story ends with a narrow miss rather than a neat sales triumph. That makes it a revealing demonstration: by the time a company is obviously ready to buy, the decision may already be made. Clean is trying to make those earlier signals easier to connect.