
How Much Does AI Hiring and Recruitment Software Cost?
AI recruitment software can screen resumes, match candidates, and automate scheduling. Here is what off-the-shelf and custom options cost and when each makes sense.
Maira Koin
CEO, F Koin Tech
Published
26 September, 2026
AI hiring and recruitment software is available as a subscription, typically priced per recruiter, per job post, or per employee, or as a custom-built platform. A custom AI recruitment tool with resume parsing, candidate matching, and an applicant pipeline often starts in the range of ₹3,00,000 to ₹8,00,000 at market rates and can go higher for job portals or multi-company platforms. Ongoing AI usage and hosting costs come on top.
Before you compare prices, be clear about which part of hiring you actually want to automate.
What AI can do in recruitment
Resume parsing: extract skills, experience, and education into structured data
Candidate matching: rank applicants against job requirements
Job description drafting: create consistent, inclusive job posts faster
Screening questions: auto-score short-answer or skills questions
Interview scheduling: coordinate calendars without email back-and-forth
Candidate communication: status updates and reminders
Subscription tool or custom build?
Choose an off-the-shelf applicant tracking system (ATS) if you hire occasionally, follow a standard process, and want something working this month.
Consider custom software if you run a staffing agency, a job portal, high-volume or regional hiring, or need hiring tied closely to your HR, payroll, or training systems. Custom tools also make sense when you want to own candidate data and build your own matching logic.
What drives the cost
Number of user roles (candidates, recruiters, hiring managers, clients)
Job board and career page integrations
AI features and how much matching logic is custom
Assessments, video interviews, or document verification
Languages and regional support
Reporting and compliance requirements
Be careful with fairness
AI screening can repeat biases found in past hiring data. Good practice includes keeping humans in the final decision, using job-relevant criteria only, regularly checking outcomes across candidate groups, and being transparent with candidates that automated tools are used.
A related example
F Koin Tech built LastKoin, a web-based resume builder with templates, customisation, and multi-format export. It shows how candidate-facing tools can make structured data easier to collect, which is the foundation of any good matching system.
If you are planning recruitment software or want to add AI to your existing hiring process, explore our custom IT and AI solutions or get in touch to discuss your workflow.



