aicvscreening
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React Complex Tree
Pagedraw - Beta release
AI CV Screening helps recruiters, founders, and hiring managers quickly process large volumes of resumes. Instead of manually reviewing hundreds of CVs, upload candidates and get ranked results with detailed insights.
How it works: - Add a job description - Upload CVs (.PDF, .DOCX, .TXT, .MD) or a .ZIP with multiple files - Automatically screen and rank candidates
Key features: - Candidate scoring based on job fit - Clear explanations (why a candidate matches or not) - Pros & cons for each CV - Extracted contact details - Sort and filter candidates - Export results to .CSV
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aicvscreening's answer
Anyone who needs to review many CVs efficiently.
aicvscreening's answer
aicvscreening's answer
AI CV Screening focuses on speed, clarity, and actionable insights, not just keyword matching.
Instead of simply filtering resumes, it: - ranks candidates by real job fit - explains why each candidate matches or doesnโt - highlights pros & cons for quick decision-making - works with multiple file formats and bulk uploads (.ZIP)
Itโs built to replace manual CV review, not just assist it.
aicvscreening's answer
Most tools are complex ATS platforms or basic keyword filters.
AI CV Screening is different because it: - requires no setup or integrations - works instantly with uploaded CVs - provides transparent scoring (not a black box) - is optimized for fast decision-making (100 โ top candidates in minutes) - offers a generous free tier (50 CVs)
Itโs ideal for teams that want results quickly without heavy systems.
aicvscreening's answer
AI CV Screening was built out of frustration with manual resume review.
Reviewing dozens (or hundreds) of CVs is repetitive, time-consuming, and often inconsistent. Even with existing tools, the process still required too much manual effort.
The goal was simple: turn CV screening into a fast, structured, and automated process
Instead of reading every resume, users can focus only on the best candidates.
aicvscreening's answer
AI CV Screening is built on a modern, AI-ready SaaS stack (based on GoLiveKit), focused on speed, scalability, and type safety.
Core technologies: - Next.js + React - full-stack framework with server-side rendering and modern UI architecture - Node.js - backend runtime for server logic - TypeScript - end-to-end type safety
Database & backend: - PostgreSQL - relational database - Prisma ORM - type-safe database access
AI layer: - AI SDK (LLM APIs) - for CV analysis, scoring, and explanations
API & data handling: - oRPC - type-safe API layer - React Query (TanStack Query) - data fetching and caching
Frontend & UI: Tailwind CSS + shadcn/ui - styling and component system - Radix UI - accessible UI primitives
Validation & quality: - Zod - schema validation - Biome - linting and formatting - Vitest - testing
Authentication & infrastructure: - Better Auth - authentication and session management - Cloud storage (S3-compatible, e.g. R2) for file uploads
This stack enables fast development, strong type safety, and seamless integration of AI features.
Based on our record, React Complex Tree seems to be more popular. It has been mentiond 2 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.
You can find the source code for it at https://github.com/lukasbach/react-complex-tree, and documentation and examples at https://rct.lukasbach.com. Source: over 3 years ago
More examples on the customizability, in-depth documentation and a typing API is available at the documentation homepage: https://rct.lukasbach.com/. Source: about 5 years ago
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