Facility Management & Staffing
This is a people-heavy, high-churn business: guards and frontline workers turn over fast, and the operating spine is filling many requisitions quickly with documented, verified people. Sourcing runs on referrals and WhatsApp, screening and police or background verification is tracked on a spreadsheet, onboarding documents (Aadhaar, PAN, bank, UAN, ESIC, photo, contract) are chased by hand and re-keyed, and the same leave, attendance and policy questions are answered over and over. A missing or expired verification or onboarding document fails the client compliance audit; a slow fill leaves a post unmanned and a contract at risk. But every decision about a person, who to hire, what to pay, who to deploy where, is a live legal-risk surface where a machine must not decide.
Who has it
Core for staffing and contract-workforce providers running requisition-to-fulfilment at volume, and for security and manpower-deployment agencies with high-churn guard hiring and verification; integrated facility-management companies and housekeeping, catering and soft-services operators run continuous frontline hiring.
What we build
Non-AI for the workflow and the numbers: a requisition-to-fulfilment pipeline (open requirement, sourcing, screening, verification, onboarding, deployment-ready) with status visible per requisition; an onboarding checklist that collects and structures the statutory documents per worker; the attendance-to-payroll-input path off the deployment record. AI helps where it is genuinely useful and bounded: answering cited Tier-1 leave, wage and policy questions from the operator's own handbook (abstaining when unsure), reading resumes and identity, bank and verification documents into structured fields, and ranking applicants to order the review queue, never to reject.
What is automated, where AI helps, who signs off
The reliable spine
The non-AI spine is the pipeline and the checklist: the requisition-to-fulfilment stages, the onboarding-document checklist and the attendance-to-payroll-input path are deterministic workflow, and the hire, the pay and the deployment decision stay with a named manager.
Where AI helps
AI is bounded to where it is genuinely useful: reading resumes and identity, bank and verification documents into structured fields, answering cited leave, wage and policy questions from the operator's own handbook and abstaining when unsure, and ranking applicants to order the review queue, never to reject; it never owns the number, the approval, the promise or the decision.
Who signs off
A named person signs off anything touching money, stock, a customer promise, a regulated filing, a payment, a price, a credit decision or a people decision.
What changes day to day
Requisitions get filled faster with documented, verified people; onboarding documents are collected and structured without the WhatsApp chase, so they are ready for the client audit; routine people queries get answered on their own; every decision about a person stays with a named manager.
Illustrative outcome
Shorter time-to-fill, a cleaner verified-document set per worker that passes the client audit, and HR time returned from chasing documents to real people work. Illustrative; final numbers come from your own data.
Illustrative; final numbers come from your own data.
Path to the build
Book a free 60-minute call, then a free Blueprint on the firm's own records. Deep-dive and build, followed by run and govern so the workflow keeps paying back.
Related builds
A free 60-minute call. No cost, no obligation, just a clear read on what is worth building.