Metaview’s AI Sourcing Agent helps you find high-fit candidates faster by searching a database of professional profile data sourced from publicly available professional profiles and licensed from professional data providers, and surfacing a ranked list of profiles based on your requirements. It reduces the time you spend on manual sourcing — but you remain in full control of who to contact, how to engage them, and every hiring decision that follows. This guide outlines best practices for using AI Sourcing responsibly and effectively.
Overview
AI Sourcing is designed to assist, not replace, your recruiting judgment.
- You describe the role you’re hiring for — through job descriptions, verbal briefs, or calibration on existing candidates.
- Metaview’s AI generates an Ideal Candidate Profile (ICP) based on your input, which is presented to you for review and approval before any search is run. You can edit, override, add, or remove any criteria in the ICP.
- The AI Sourcing Agent searches the candidate database to identify people who may be a good fit, and returns a ranked list of candidate profiles that you can re-sort, search, and filter.
- You independently review the results and decide who to contact and how to proceed.
Metaview AI Sourcing does not:
- Make hiring decisions or recommendations about who to hire.
- Automatically contact, progress, or reject any candidate.
- Recommend specific actions to take on any candidate.
- Use protected characteristics in ranking candidates.
- Replace your team’s independent evaluation of candidates.
Defining your search criteria
The quality of your sourcing results depends on the clarity of your inputs. When you describe what you’re looking for, Metaview generates a structured Ideal Candidate Profile (ICP) that breaks your requirements into clear, weighted sections — including must-have qualifications, nice-to-haves, target companies, and anti-patterns. This structure is designed so you can see exactly how each criterion is being weighted before the search runs.
You review and approve the ICP before any search is executed, and can edit any part of it. Best practice guidelines for search criteria:
- Be specific about what matters for the role. Include relevant skills, experience levels, and role-specific requirements rather than broad or vague descriptions.
- Focus on job-related qualifications. Keep your criteria centered on professional attributes like skills, experience, career history, and location relevance.
- Calibrate when possible. Use existing strong candidates or profiles as calibration examples to help the AI understand what “good” looks like for this specific role.
- Iterate and refine. If initial results aren’t quite right, adjust your criteria. Calibration feedback refines results within your current search session.
- Avoid criteria that could introduce bias. Do not include references to protected characteristics such as age, gender, ethnicity, disability, or other non-job-related personal attributes in your search requirements.
If your initial results feel too broad, narrow your criteria by adding required skills, seniority bands, or industry context. If they feel too narrow, remove overly restrictive requirements and recalibrate with a few example profiles.
Reviewing and acting on results
Every list of candidates Metaview surfaces is a starting point for your review — not a final answer. The ranking reflects how closely each candidate’s profile matches the requirements you’ve set, but your judgment is what determines who moves forward.
When reviewing your results, you can:
- Evaluate candidates independently. Don’t rely solely on ranking position. Review individual profiles to assess fit based on the full context of the role.
- Use the results as one input among several. Combine AI Sourcing results with other sourcing channels, referrals, inbound applications, and your own research.
- Consider candidates the AI may have ranked lower. Rankings reflect pattern matching against your criteria — they may not capture every dimension of what makes a great hire.
- Document your reasoning. When you decide to progress or pass on a candidate, note why. This supports fair, consistent decision-making across your team.
All downstream decisions — including whether to contact a candidate, schedule an interview, add them to your ATS, or extend an offer — are made entirely by you and your hiring team. Metaview’s role ends at surfacing and ranking candidates.
Rankings indicate relevance to your stated criteria — not overall candidate quality. Always assess candidates against the full scope of role requirements and team needs.
Candidate outreach
When you reach out to candidates, your organisation is the data controller for that outreach. If you request contact details (email address or phone number) for a candidate, these are obtained on your behalf from contact enrichment services — they are not part of the candidate’s original profile data.
Two things to include in every outreach communication:
- Link to your organisation’s privacy policy. This lets candidates know how their data is being used and what their rights are.
- Include an unsubscribe or opt-out mechanism. Give candidates a simple way to tell you they don’t want to be contacted, and honour those requests promptly.
If a candidate asks not to be contacted, that is your responsibility to action — Metaview provides the tooling, but managing outreach preferences sits with your team.
Data sources
Metaview AI Sourcing searches a database of professional profile information — such as career history, skills, professional experience, and education — sourced from publicly available professional profiles and licensed from professional data providers. Metaview maintains this data under its own privacy policy.
Where you take action within the platform — saving candidates, adding notes, requesting contact details, or initiating outreach — Metaview processes that activity on your instruction under your data processing agreement. All activities you take on presented candidates — reviewing candidates, reaching out, and making hiring decisions — are entirely within your organisation’s control.
Fairness and bias testing
Metaview operates a bias testing programme to identify and reduce the risk of demographic bias in search results. This includes testing before each model deployment and ongoing monitoring of live outputs. The programme evaluates the model’s own ranking behaviour — whether it introduces or amplifies disparity when executing a search against a given set of criteria. The criteria you choose to include in your ICP are your responsibility.
Privacy considerations
Metaview has designed its AI Sourcing product to comply with applicable data protection and AI regulations, including emerging AI governance frameworks. However, regulations vary by jurisdiction and your organisation should seek independent legal advice for your specific regulatory obligations and use cases.
You’re always in control
Metaview AI Sourcing is designed to make your sourcing faster and more effective while keeping you firmly in control. The AI searches and ranks — you decide and act. No candidate is contacted, progressed, or rejected without a human making that choice.
By combining AI-powered sourcing with your professional judgment and responsible outreach practices, you can build stronger pipelines while ensuring that every step of the process is fair, transparent, and human-led. 
