The Hardest-to-Find Buyers Are the Most Valuable Ones

01 /The Concept

Leadbay claims its AI engine helps companies find potential buyers among small and mid-sized businesses – ones no other lead-generation platform can surface.

The startup targets companies of all sizes that sell into the large but fragmented SMB market across the US and France. (France is in the mix because that's where Leadbay was founded)

To get started, a company uploads its historical prospect list to the platform – tagging which companies converted and which didn't.

The AI then generates a new list of potential buyers, with Leadbay promising that more than 55% of them will be names the company has never encountered before.

One notable feature is the concept of "lenses" – separate workspaces for uploading and receiving different lead sets. This is useful when a company sells multiple products to distinct audiences, since each scenario requires training the AI on a different data set.

Early customers are already reporting striking results.

A wholesale distributor of construction finishing materials says the number of new clients per sales rep has doubled. It has even landed accounts whose purchasing volume mirrors the history of its top-10 existing clients.

A B2B supplier of hardware to furniture assemblers reports that its reps are booking meetings with 85% of the leads the platform surfaces – a strong signal of relevance. The result: revenue in 10 months that previously took four years to accumulate.

Clients from other sectors – a hospitality and restaurant supplies wholesaler, an SMB insurance broker, a staffing agency, and a packaging materials vendor – have also started using the platform, with results still pending announcement.

The first 50 leads are free so companies can validate quality before committing. Standard plans run $169 or $399 per sales rep per month, depending on the monthly lead volume required. High-volume enterprise customers negotiate pricing directly.

Leadbay was founded in 2023 but operated only in France before raising any outside capital. It has since entered Y Combinator to accelerate product development and expand into the US before targeting global markets.

02 /Why It Matters

It's worth pausing on what Leadbay actually asks customers to upload: the full historical prospect list – both wins and losses. Most comparable platforms, including social-media lookalike audience tools, only ask for existing customer lists.

That distinction is the whole point. Leadbay's goal isn't to generate the longest possible list of companies that might buy something. It's to generate the shortest list with the highest probability of closing. To do that, the AI needs negative examples as well as positive ones – so it can exclude companies that look right on paper but rarely convert.

The business case is stark: sales reps today spend roughly 70% of their time on prospects that never buy. That means companies are burning 70% of their sales payroll on dead ends, while simultaneously losing 70% of the revenue they could have generated with better-qualified leads.

Leadbay's answer is to optimize existing sales teams rather than grow headcount – giving reps fewer, better targets. The startup claims its AI can predict deal success or failure with 96% accuracy in advance.

What makes this credible is the mechanism behind it. Leadbay's AI doesn't rely primarily on scraped online signals about target companies – the startup openly argues that online signals alone can't predict sales outcomes with sufficient precision.

Instead, the engine analyzes the real historical decisions of real sales reps: who they actually closed, and who they couldn't. The AI tries to encode the intuition of experienced salespeople and apply it at scale. The result isn't a replacement for human judgment – it's an amplifier of it.

That approach has an added edge: the AI can score a lead even when very little public data exists about that company. Where other platforms hit a dead end with sparse information, Leadbay can still infer fit based on learned sales-rep intuition.

Leadbay's broader thesis is that AI should be a co-pilot for salespeople, not an autopilot. If that framing is right, AI threatens business development departments – whose job is to identify new customer categories – more than it threatens individual reps.

The startup places particular emphasis on the "real" economy: offline businesses that have only a faint digital footprint, making them hard to analyze with conventional methods.

This framing echoes Resquared ([related review](/review/zarabatyvaj-na-teh-kogo-trudno-najti)), which raised $5 million last summer on a platform for finding local small businesses as customers. Resquared points out that 60% of US businesses have no LinkedIn presence – and 90% of small businesses are invisible there entirely. The hard-to-find segment is structurally underserved.

Throxy ([related review](/review/pravilno-vybrannaja-model-raboty-startapa-srazu-otsekaet-kuchu-konkurentov)) raised $6.2 million in September on a platform similarly targeting SMB markets that resist traditional analysis – pulling from niche data sources like board membership registries and product certification databases. Throxy is so confident in its lead quality that it charges per meeting booked rather than per lead delivered.

03 /Opportunities

The central trend here is platforms that help companies find buyers who are genuinely hard to find.

The business logic is elegant: hard-to-find buyers are a blue ocean by definition. If a prospect is difficult to identify, most vendors simply skip them – their lead lists are built from the same obvious suspects everyone else is targeting. That creates a red ocean around easy-to-find prospects and a comparatively calm one everywhere else.

The differentiator, then, is data sources and the algorithms used to work them. Three details from this review are worth keeping in mind:

- Prioritize companies with a thin online presence rather than chasing the most data-rich targets.

- Amplify the intuition of real salespeople instead of relying purely on AI that may lack sufficient signal to work from.

- Optimize sales rep time rather than inflate the lead list – the goal is a higher close rate, not a longer pipeline.

Where in your own market are the buyers that are genuinely difficult to find? Or conversely – where do you already know hard-to-find buyers exist, and who among sellers needs them most?

For a while it seemed like the blue ocean was a myth – competition had intensified to the point where everyone was selling to everyone. But it's starting to look like blue oceans still exist – you just have to find them in very different places than before.