OPAL is an agentic AI recruitment platform built for Malaysian recruitment agencies and HR teams. From JD creation to onboarding — fully automated, deeply integrated, and designed for how Malaysian hiring actually works.
OPAL Beta — Limited Access Open
We are currently onboarding a select group of Malaysian recruitment agencies and HR teams onto the OPAL beta programme. Beta participants get priority onboarding, direct access to our product team, and preferential pricing when OPAL launches commercially.
The Reality
Most organisations have accepted manual screening, inconsistent scoring, and slow time-to-fill as normal. It isn't normal — it's just familiar.
45–60 days
Average time-to-fill in Malaysia
Every empty seat has a daily productivity cost
8–15 hours
Recruiter time per role on screening alone
Multiplied across 10 open roles simultaneously
RM8k–25k
Average cost per hire in Malaysia
Depending on seniority and recruitment method
0
Standardised scoring rubrics in most agencies
Two recruiters, same CV — two different outcomes
The Full Workflow
OPAL covers the entire hiring lifecycle in a single connected pipeline. Each step hands off automatically to the next.
The JD Clarity Bot guides hiring managers through structured questions and generates a complete, well-written job description in minutes — not days.
Post to JobStreet, LinkedIn, Monster and other portals simultaneously from a single interface — no copy-paste, no manual logins.
AI agents automatically search, identify, and shortlist top candidates from multiple job portals based on your role requirements — without manual searching.
Screenshot: Sourcing agent results and candidate list
Every incoming CV is scored against a structured rubric derived from the JD. Two-tier LLM pipeline: fast filter then deep evaluation. Each candidate gets a documented score — not a gut feel.
Screenshot: CV scoring dashboard with scores and justifications
Recruiters see a ranked shortlist with scores and evidence — not a pile of 200 unsorted CVs. The top candidates are immediately obvious.
For each shortlisted candidate, OPAL generates personalised interview questions based on gaps and strengths identified during CV scoring. Structured summaries produced automatically post-interview.
Screenshot: Interview question generator and summary output
Real-time visibility into your entire pipeline — time to hire, drop-off rates, source performance, and candidate quality metrics. No more Excel tracking sheets.
Screenshot: Hiring analytics dashboard
Automate the entire onboarding journey from offer letter to day one — document collection, IT setup requests, and induction scheduling handled automatically.
Screenshot: Onboarding workflow automation view
Features & Capabilities
From sourcing to onboarding — OPAL combines intelligent automation, specialist AI bots, and deep integrations into a single recruitment toolkit.
AI agents that mimic human recruiter behaviour — logging into job portals, searching for candidates, shortlisting profiles, and downloading CVs directly into the scoring pipeline. No manual searching, no copy-paste, no missed candidates.
Our inference engine reads CVs the way a senior recruiter would — not keyword matching like a typical ATS black box. Every candidate gets a score plus documented reasoning: strengths, weaknesses, skill gaps, and a clear recommendation on whether to interview. Explainable, auditable, and consistent across every single CV.
Real-time pipeline visibility — time to hire, source performance, drop-off rates, and candidate quality metrics across all active roles and recruiters.
From offer letter to day one — document collection, IT setup requests, and induction scheduling handled automatically so new hires start without friction.
Converts your JD into a polished, ready-to-publish job post for LinkedIn, JobStreet, and your ATS. Automatically structures the company intro, role summary, requirements, benefits, and SEO-friendly hashtags.
Reformats raw CVs into your official branded Word template automatically. Standardises layout across all candidate submissions — skills, experience, education — without losing a single line of original content.
Creates a complete hiring playbook per role — target companies, sourcing channels, budget estimates, and timelines. Especially powerful for hard-to-fill specialist and leadership roles.
Guides hiring managers through structured questions and generates a complete, well-written job description in minutes. Separates must-have from nice-to-have criteria and flags vague or conflicting requirements before they cause rework downstream.
Generates personalised interview questions for each shortlisted candidate based on their CV scoring results — highlighting gaps to probe and strengths to validate. Produces structured interview summaries automatically for consistent hiring decisions.
Who OPAL Is For
Integrations
OPAL layers on top of your existing ATS or operates standalone. No ripping out your current stack.
Manatal
ATS — Deep integration
Workday
ATS — Integration available
SAP SuccessFactors
ATS — Integration available
JobStreet
Job Portal — Sourcing agent
Job Portal — Sourcing agent
Monster
Job Portal — Sourcing agent
Any ATS
REST API integration
Any Portal
Agentic sourcing
FAQ
OPAL is an agentic AI recruitment platform built for Malaysian recruitment agencies and corporate HR & talent acquisition teams. It automates the full hiring lifecycle — from JD creation and job posting to CV scoring, candidate ranking, interview preparation, and onboarding.
Yes. OPAL is designed to integrate with your existing ATS including Manatal, Workday, SAP SuccessFactors, and others. It can also operate as a standalone recruitment platform for teams that don't currently use an ATS.
OPAL uses an agentic sourcing approach that can work across any job portal — including JobStreet, LinkedIn, and Monster — rather than being locked to a fixed set of integrations. This means your sourcing coverage expands as the agent evolves.
OPAL uses a two-tier LLM scoring pipeline. A fast first-pass model screens all incoming CVs against your job criteria and filters out clear mismatches. A more powerful second-pass model then performs deep rubric-based evaluation on promising candidates, generating a score with documented justification for each.
OPAL is currently in beta with selected Malaysian recruitment agencies and HR teams. We are accepting applications to join the beta programme. Contact us to discuss your hiring volume and use case.
Beta Access Open
Beta participants get priority onboarding, direct access to our product team, and preferential pricing at commercial launch. Limited spots available.