HR and recruitment teams share one underlying challenge: too much repetitive work standing between them and the people-focused parts of their job. Sorting resumes, coordinating interviews, and answering the same policy questions consume hours every week. At ShatarupaX AI Labs we build AI recruitment automation and HR workflow automation around each client's own process — automating the administrative load, surfacing information faster, and giving teams more time to actually talk to candidates and employees.
AI resume parsing extracts skills, experience, and qualifications, then matches candidates against job requirements. AI does not make hiring decisions on its own — it surfaces the most relevant profiles for human review.
Compares candidate skills, experience, and qualifications against job requirements to help recruiters identify strong fits faster.
Drafts job postings and requirements in less time, giving recruiters a strong starting point for every requisition.
Supports interview scheduling, reminders, transcription, and question preparation so hiring teams stay consistent. AI organizes information for reviewers — it never independently decides whether a candidate is hired.
Handles candidate questions, application status updates, and interview scheduling around the clock.
Supports employees with everyday questions — policies, leave, and benefits — reducing repetitive tickets landing in the HR inbox.
We learn the current HR or recruitment workflow, pain points, users, and existing systems before proposing anything.
We assess where automation, screening, matching, or analytics genuinely add value — and where they won't.
Architecture, workflow design, data flow, integrations, and human review checkpoints.
Cleaning resume data, job descriptions, and HR knowledge bases, handled according to the organization's own data policies.
Development against real workflow behavior and edge cases, then integration with your ATS, HRIS, or HRMS.
Ongoing performance monitoring and workflow optimization as your hiring needs change.
High-volume screening is where hiring quality silently degrades: the first hundred resumes get read carefully and the next seven hundred get skimmed. Consistent, criteria-based screening applied to every applicant is fairer than a tired recruiter at 6pm — but only if the criteria are explicit and the reasoning is auditable. That's the part most tools skip.
The system narrows and explains. People decide.
Standardize repetitive HR processes across large, distributed teams
Hire efficiently without building a large in-house recruiting function
Place candidates faster across multiple open roles
Manage high application volumes for multiple clients at once
Reduce the volume of repetitive employee queries
Keep candidates informed and engaged throughout the process
HR and recruitment involve people and sensitive personal information, so responsible AI matters here more than almost anywhere else:
We don't claim legal compliance unless it's been specifically verified for a client's context, and we don't provide legal advice — organizations should involve their own legal and compliance teams for jurisdiction-specific requirements.
No. It ranks and explains; it does not decide. Every candidate remains visible to the recruiter along with the reasoning behind their position, so a human makes the call on who progresses.
AI resume screening can parse resumes, extract skills and experience, and rank candidates against job requirements — though final hiring decisions should always involve human review.
Ranking runs against criteria the hiring manager states explicitly, and we avoid attributes that act as proxies for protected characteristics. A rationale is logged for every candidate so screening patterns can be audited.
In most cases, yes — we assess integration requirements during the design phase and confirm compatibility with specific platforms before implementation.
