Spott Raises $21M for Expansion; Placements Are the Test

On September 22, 2026, Leuven-based Spott announced a $21M Series A led by Balderton Capital, with Base10 Partners, Y Combinator and Fortino participating. The round brought its disclosed funding to $24.2 million after a $3.2 million seed. More than 500 recruitment agencies use Spott, and the new capital is intended for international expansion, enterprise features and more proactive AI capabilities.

New York and Sydney are the immediate expansion priorities. Tech.eu’s account of the financing quotes co-founder and CEO Lander Degreve saying, “Recruitment succeeds through trust and human judgement.” The commercial question is whether Spott can help agencies complete more placements as it grows beyond its early customer base.

The round funds a broader agency system

Spott combines applicant tracking, customer relationship management, search, conversations, outreach and automation in one platform. Agencies can search information held in CVs, emails and recruitment pipelines, including details that may have been buried in earlier exchanges. For a recruiter, that can make an existing candidate relevant to a new vacancy without requiring someone to remember where the original conversation was stored.

The planned product work extends beyond retrieving records. Spott intends to develop AI capabilities that surface vacancies, candidate career moves and recommended next steps before a recruiter begins a search. Its enterprise work is aimed at agencies operating across countries. Recruiters remain responsible for consequential choices: the platform does not autonomously move candidates into pipelines or present them to clients without human approval.

Revenue and customers show where expansion starts

Spott’s revenue has grown more than tenfold since the start of 2026, though it has not disclosed the starting or current revenue figure. Balderton’s account of the round puts approximately 20% of revenue in APAC and 15% in the US, describes a plan to grow the workforce from 44 to around 60 by year-end, and cites customer data indicating up to 30% more placements. Those regional shares describe revenue from broad markets, rather than revenue attributable to the planned offices.

The customer examples show different demands on the system. At H.W. Anderson, more than 100,000 candidate profiles and years of conversations became searchable, giving recruiters access to information already held by the agency. CGP Group, an agency with 200 people, rolled out Spott across 12 countries. One example concerns recovering useful candidate history; the other concerns running the platform across a distributed organization.

Those examples make the expansion more concrete, but they do not establish a typical rollout cost or a typical placement gain. Revenue growth also needs a denominator: a tenfold increase describes the pace of change without showing how much the business earns. The regional mix demonstrates that Spott already has business outside its home market, while leaving the size and durability of that revenue undisclosed.

The placement gain is a customer-reported upper bound

The placement improvement comes from customer data cited by the company and its investor; no independent audit or agency-wide distribution accompanies the public claim. “Up to” identifies the high end of a reported outcome. It does not tell an agency how many customers achieved an improvement, what their starting placement rates were, or how long the improvement lasted.

Those distinctions matter because agencies begin with different records and workflows. Making old candidate conversations searchable could be especially valuable where recruiters have a large store of dormant information. An agency with cleaner records may see a smaller change, while a complex rollout may require more work to move data and train staff. The published customer examples do not provide a common baseline that would allow those situations to be compared.

A completed placement also depends on the recruiter’s judgement and the client’s hiring decision. Spott’s human approval requirement keeps those decisions with the agency, so placement output measures the combined workflow rather than the software in isolation. Retention, implementation effort and results across agencies of different sizes would give a clearer picture of whether the reported gain travels beyond the strongest early cases.

New York and Sydney put the rollout to a wider test

Building local teams in New York and Sydney should give Spott more capacity to sell, onboard and support agencies in the markets it is targeting. The enterprise roadmap raises a related test: whether the platform can keep candidate information useful across teams and countries while preserving recruiter control over submissions. Larger deployments may reveal demands that are less visible in a single agency’s database.

The next meaningful evidence will come from sustained placements and retained customers after those international rollouts. As the planned offices and enterprise features develop, results across a wider range of agencies will show whether Spott’s expansion is translating into repeatable recruitment outcomes.