Split Fee is a platform for UK recruitment agencies to collaborate on permanent placements.
Every agency has candidates they can't place and vacancies they can't fill. Another agency almost certainly has what you need โ but finding them, trusting them, and making the collaboration work has always been the hard part.
Split Fee solves this. Post your candidates and vacancies to the platform. Our matching algorithm finds opportunities across every agency on the network โ by skills, location, salary, and seniority. Candidate and client data stays anonymised until both sides agree to work together. When a placement is made, we handle the fee split and invoicing automatically.
No more posting in social media groups and hoping someone replies. No more sharing candidate details with strangers on trust alone. No more chasing invoices from agencies you barely know.
45% for you. 45% for them. 10% platform fee โ only when a placement is made.
Half of a placement fee is infinitely better than none of it.
A startup from the United Kingdom that is founded by Abbie Taylor.
A next-generation serverless platform, built for AWS.
Split Fee is the first purpose-built platform for split fee recruitment in the UK. Instead of relying on LinkedIn groups, WhatsApp messages, and manual agreements, agencies upload their candidates and vacancies and the platform automatically matches them across agencies.
Candidate identities are revealed gradually; anonymised at first, then progressively disclosed as both sides accept, so agencies can collaborate without the risk of circumvention.
Most "split fee networks" are just directories or social groups where agencies post and hope someone responds. Split Fee is an actual matching engine. It scores candidate-vacancy pairs, handles the legal agreements (non-circumvention, self-billing), automates invoicing and fee splits, and manages the entire placement lifecycle from match to payment. Everything that normally requires trust, phone calls, and spreadsheets is handled by the platform.
UK recruitment agencies; from boutique firms with a handful of consultants to mid-sized agencies with specialist sector coverage. Any agency that has either strong candidates without the right vacancies, or client vacancies they can't fill from their own candidate pool. Split Fee turns those dormant assets into placements.
Abbie, our founder, knew that although split fee arrangements have existed in recruitment for decades, the process has always been manual: find a partner agency, negotiate terms, trust them with your candidate data, chase invoices. Most agencies avoid it because the overhead and risk outweigh the reward. Abbie built Split Fee to remove that friction entirely, with automated matching, progressive identity disclosure, built-in legal agreements, and automated billing, making split placements as straightforward as direct ones.
Split Fee (split-fee.com) appears to be a niche referral/fee-splitting platform aimed at connecting professionalsโlikely in real estate, legal, or brokerage-type industriesโto share commissions on referred deals. Without independent reviews or verified track record widely available, it should be approached with due diligence, but the concept itself addresses a real market need for structured referral partnerships.
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Check the traffic stats of Split Fee on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of Split Fee on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of Split Fee's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of Split Fee on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
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