aicvscreening's answer:

• Startup founders hiring quickly
• Recruiters handling high volumes of applicants
• Small and mid-sized teams without complex ATS systems
• Hiring managers who want to save time on initial screening

Anyone who needs to review many CVs efficiently.

aicvscreening's answer:

• Early-stage startups
• Indie founders
• Small recruiting agencies
• Tech hiring managers

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 doesn’t - highlights pros & cons for quick decision-making - works with multiple file formats and bulk uploads (.ZIP)

It’s 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 → top candidates in minutes) - offers a generous free tier (50 CVs)

It’s 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.