
DianApps played a key role in building Hirenetix AI’s end-to-end web platform, focusing on performance, automation, and scalability. Our team developed a modern Next.js front end for HR dashboards and candidate workflows, robust Node.js backend services for hiring operations, and integrated an AI engine powered by Python and Gemini-induced APIs to enable resume screening, candidate scoring, and automated decision-making. This collaboration resulted in a smart hiring platform that reduces recruiter workload while improving hiring speed, accuracy, and consistency.

1
Manual resume reviews took 5–10 minutes per resume and required extensive recruiter effort.
2
Candidate scoring was inconsistent and biased, taking 30–60 minutes per candidate.
3
Interview scheduling and follow-ups were handled manually, increasing delays.
4
Time-to-hire typically ranged from 2–4 weeks, slowing talent acquisition.
5
High recruiter and administrative costs due to manual processes.
1
AI-powered resume screening instantly evaluates resumes without manual intervention.
2
AI-driven scoring and auto-ranking deliver up to 90% accuracy with consistent evaluations.
3
Automated shortlisting, interview scheduling, and follow-ups streamlined the entire workflow.
4
Automation reduced time-to-hire to just 3–5 days.
5
Automated workflows reduced cost per hire by up to 80%.
Hirenetix AI significantly improved the hiring experience by replacing manual recruitment tasks with automated, AI-driven workflows. Organizations using the platform benefit from faster hiring cycles, reduced operational overhead, consistent candidate evaluations, and the ability to scale recruitment efforts efficiently without increasing manual oversight.
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