Distill
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Split Fee
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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.
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Split Fee's answer:
A next-generation serverless platform, built for AWS.
Split Fee's answer:
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.
Split Fee's answer:
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.
Split Fee's answer:
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.
Split Fee's answer:
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.
Based on our record, Distill seems to be more popular. It has been mentiond 26 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I love reading articles written at Distill (http://distill.pub/), but due to its indefinite hiatus (https://distill.pub/2021/distill-hiatus), I am looking for other online free resources which host such interactive, interesting and engaging material. Does anyone know about any such websites? - Source: Hacker News / over 1 year ago
Distill was a new take at publishing research/ideas in deep learning in a visual way: https://distill.pub/ I love their articles and while it was hard to sustain, the quality of the ones in their are pretty good. They provide some tips and templates on how to develop such visual storytelling articles. - Source: Hacker News / almost 3 years ago
Explainable AI is far from early stages. Read into anthropic aiโs work in mechanistic interpretability like toy models of superposition along with the rest of the transformer-circuits papers. Read chris olahโs distill papers. Read neel nandaโs recent work on reverse engineering how language models grok modular addition. Read kevin mengโs work on locating and editing facts inside of gpt. Read openaiโs paper on... Source: about 3 years ago
I also wasn't aware of either The Pudding or distill.pub. So thanks for just mentioning those. Source: over 3 years ago
Anything from Setosa [0] is really good. It contains interactive, animated illustrations of several Machine Learning ideas. I _loved_ reading papers from Distill Pub [1] as they contained interactive diagrams. My most favorite one so far is the thread on Differentiable Self-organizing Systems [2]. I liked the lizard example very much as it is interactive, and lizards grow lost organs back. I think this is funny.... - Source: Hacker News / over 3 years ago
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