
LinearB
Waydev
Swarmia
CodeClimate
GitPrime
Haystack Analytics
Codacy
SonarQube
aicvscreening
Workable
Ashby
Recruitee
Careerkit
HireVue
Zoho Recruit
JobFitCV
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
LinearB
aicvscreeningLinearB is recommended for software development teams, engineering managers, and project managers who want to improve visibility into their development processes, reduce cycle times, and boost overall productivity. It's particularly useful for teams that rely on agile methodologies and need to continuously monitor and improve their workflow efficiency.
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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, LinearB seems to be more popular. It has been mentiond 28 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.
LinearB is an engineering productivity platform that provides visibility into developer workflows, automation, and process metrics. It collects data across the entire development lifecycle to diagnose blockers and optimize delivery. One user reports saving 321 developer-hours per month. - Source: dev.to / 3 months ago
Most tools measure half the picture. Traditional metrics platforms like LinearB focus on quantitative signals (DORA metrics, cycle time). Survey platforms like Culture Amp capture sentiment across organizations but aren't developer-specific. DX (founded by DORA/SPACE research creators) combines developer surveys with SDLC analytics. These approaches require deliberate implementation and buy-in. - Source: dev.to / 8 months ago
LinearB is a SaaS solution that retrieves metrics overtime, some of them being used to calculate DORA Metrics. They also have a Youtube channel that advocate for DORA Metrics and more. - Source: dev.to / over 2 years ago
In helping engineering orgs get visibility into developer workflows with LinearB, Dan Lines and Ori Keren discovered that the majority of cycle time was being spent in pull request and code review. They found that:. - Source: dev.to / about 3 years ago
LinearB and there are a few cheaper alternatives. Ties in DORA metrics from gut repos and agile project management tools like JIRA. https://linearb.io. Source: about 3 years ago
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