Datavisual.app's answer

The frontend is built with React, TypeScript, Vite, and TailwindCSS, using Apache ECharts for rendering 30+ chart types. AI features are powered by Google Gemini. The backend runs on Python with FastAPI, SQLAlchemy, and a Supabase PostgreSQL database. The app is hosted on Vercel with PWA support for offline use. Payments are handled through Lemon Squeezy.

Split Fee's answer:

A next-generation serverless platform, built for AWS.

Datavisual.app's answer

DataViz Platform combines 30+ interactive chart types with AI-powered chart generation in a single free tool. You can describe a chart in plain English and have it built instantly, or let the AI analyze your data and suggest the best visualization. Unlike most competitors, all core features — including dashboards, exports, and multi-language support — are completely free with no trial limits or paywalls.

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.

Datavisual.app's answer

Unlike Tableau or Power BI, DataViz requires no installation, no subscription, and no learning curve. You upload a CSV, pick a chart (or let AI pick for you), and you're done in seconds. It's browser-based, works on any device, and supports dark mode, PWA offline access, and 4 languages. For users who need quick, beautiful visualizations without enterprise complexity, DataViz is the fastest path from data to chart.

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.

Datavisual.app's answer

Students and researchers who need to visualize project data quickly. Data analysts who want beautiful charts without Excel's limitations. Developers looking for a free, open-source charting tool. Small teams and freelancers who can't justify enterprise BI subscriptions. Essentially, anyone who has a spreadsheet and needs a chart — fast.

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.

Datavisual.app's answer

DataViz was born out of frustration with how complicated data visualization tools had become. Most tools require expensive licenses, steep learning curves, or coding knowledge. We wanted to build something anyone could use — upload a file, get a beautiful chart, done. We added AI to make it even easier: just describe what you want in plain English. Built by LibLab, DataViz is free and open source because we believe data visualization should be accessible to everyone.

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.

Datavisual.app's answer

Individual data analysts and researchers University students across multiple countries Freelance developers and consultants