LeapRows's answer

• Zero setup: No installation, no Python environment, no SQL knowledge required. Just open your browser and drop your CSV.
• Beyond aggregation: Other tools can query large datasets, but LeapRows goes further — it lets you automate and reuse your entire data prep workflow through the Recipe feature.

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.

LeapRows's answer

LeapRows is a fully local, browser-based data tool powered by DuckDB-WASM that handles 1M+ row CSV files with blazing speed — no server, no uploads.

• Recipes: Save your entire workflow and replay it instantly on any new file, eliminating repetitive manual work.
• Smart Join: Perform VLOOKUP-style joins without any code. Composite key joins across multiple columns are supported out of the box.

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.

LeapRows's answer

• Marketers and SEO professionals who regularly work with large CSV exports (Ahrefs, Google Search Console, GA4, etc.) and find Excel or Google Sheets too slow or unstable for files with hundreds of thousands of rows.
• Engineers and data analysts who find it overkill to spin up a Python environment or database just to do a quick aggregation or data cleanup.

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.

LeapRows's answer

LeapRows was born out of two frustrations: the "Python sharing problem" and server costs.

As an in-house SEO specialist, I frequently work with large CSVs exported from tools like Ahrefs, Google Search Console, and BigQuery — often hundreds of thousands of rows. For heavy lifting, I'd reach for Python (Polars), but Python has a steep barrier: environment setup, code adjustments, and a learning curve that made it impossible to share with non-engineer teammates.

Even for myself, I'd often think "do I really need to write Python just for this small transformation?" On top of that, frustrating edge cases — like type inference inconsistencies causing join errors on the same CSV from the same tool — kept piling up.

I wanted something as easy as a spreadsheet but capable of handling millions of rows. That's what LeapRows is.

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.

LeapRows's answer

DuckDB-WASM, OPFS（Origin Private File System）

Split Fee's answer:

A next-generation serverless platform, built for AWS.

LeapRows's answer

• Currently in Beta with no notable enterprise customers yet.