Why we built TalentSourcer AI
From candidate research to a shortlist you can review. Why we built TalentSourcer AI around the agency recruiter's brief and judgment.
A search can give you a long list of candidates with the right job title. The harder question is whether their experience matches your client's brief.
Who have they sold to? Which products have they worked on? Does their profile describe the experience your client needs, or does it leave you guessing?
TalentSourcer AI grew out of recruiting and sourcing work through Talmore+. The problem was the research between finding a profile and deciding whether to contact that person. Recruiters had to investigate employers, compare experience with the brief, and record what supported each assessment.
We built TalentSourcer AI to do that first research pass and give recruiters findings they can inspect.
The research behind a shortlist
Consider a client looking for an account executive who has sold cybersecurity software to enterprise buyers.
A matching title is a starting point. You still need to know what the candidate sold, which customers they worked with, and whether they owned the sales cycle. A company website might explain the product and market. The candidate's profile might describe their responsibilities. Sometimes neither provides enough detail.
Those distinctions matter. Working for a cybersecurity company does not prove that someone sold its product. Working near a client's office does not establish willingness to commute. Missing information is a question to investigate, rather than proof of a mismatch.
Start with your client's requirements
TalentSourcer AI researches candidate profiles and employers against the requirements you define. You decide which criteria are must-haves, which are preferences, and what counts as relevant experience.
The resulting assessment shows the evidence behind each finding and flags gaps. A requirement can be met, partly met, not met, or unknown from the available information.
The score helps you compare candidates against the brief. It is not a prediction of who will get hired. Read it alongside evidence coverage and any must-have gaps.
Keep the recruiter in the decision
You may know something the available profile does not show. Perhaps a candidate explained their responsibilities on a call, or your own research uncovered relevant work.
You can add those findings and review the assessment before building your shortlist. The point is to make the research easier to inspect and use, while keeping your judgment in the process.
A researched shortlist is still a pre-outreach decision. It does not establish interest, availability or suitability for an offer. Those questions need a conversation with the candidate.
Put it to work on a real assignment
Start with a role you are working on now. Define the client's requirements, bring in a candidate pool, and review the findings against what you already know.
Look at a promising candidate, a clear mismatch and a profile with unanswered questions. Can you see why each assessment was made? What would you verify before reaching out?
That is a useful way to judge whether TalentSourcer AI fits your agency's work.
Paid plans include managed AI for candidate checks. You can connect your own API key if you prefer; external provider charges are separate. The pricing page explains the current allowances and the first-payment Basic guarantee.
Want to discuss your assignment first? Book a demo with Manu, or read more about TalentSourcer AI.