The NearTalent STAR-Agentic Method
A proprietary 21-business-day protocol that combines three layers no competitor combines: AI agentic sourcing that amplifies our 25,000+ pre-screened pool, STAR + competency interviewing that replaces casual chats with a replicable framework, and human curation by a Chief Talent Officer with 15+ years of screening experience.
Three layers. One replicable protocol.
Most nearshore competitors sit at one of two extremes. Marketplaces surface profiles algorithmically and leave the vetting to you. Traditional agencies do 100% manual scouting that takes 6-8 weeks. We built a third path: AI amplifies the reach; humans make the call.
- Layer 1 — AI Agentic Sourcing. Our proprietary agentic AI layer scans and ranks our 25,000+ pre-screened pool plus active market signals. It doesn't decide who advances — it surfaces the top 30-50 candidates who deserve human attention.
- Layer 2 — STAR + Competency Interviewing. Every finalist is interviewed by our senior team using the structured STAR framework (Situation, Task, Action, Result), combined with a competency scorecard we build with you on day 1. No casual chats. Replicable protocol.
- Layer 3 — Human Curation. Professional references are validated. The final shortlist is curated by Pamela Herrera (Chief Talent Officer) or a senior of her team. Fifteen-plus years of screening turned into a signature.
The 21-day timeline, day by day
Median measured across 1,000+ placements since 2016. Individual roles vary. What does not vary: the protocol below.
We build the competency scorecard with you
60-90 min discovery. Role, seniority, tech stack, timezone constraints, must-have vs nice-to-have, cultural fit signals, salary band, legal model (contractor / EOR / AOR). Output: written brief and a role-specific competency scorecard we both sign off on.
Agentic layer amplifies the 25,000+ pool
Our AI agents scan the pool + live market signals, rank preliminary matches against the competency scorecard, and surface the top 30-50 candidates. The AI does not decide who advances. It compresses days of manual sourcing into hours so humans spend their time where it matters.
Every finalist interviewed with a replicable protocol
Structured STAR interviews (Situation, Task, Action, Result) on 3-4 core competencies from the scorecard. Each answer scored 1-5 with evidence quoted from the candidate's response. Professional references validated in parallel. Written interview notes attached to every finalist.
3-5 finalists, each with a decision packet
Curated shortlist to your inbox: profile, STAR interview notes, competency scoring, salary expectation, availability, references validated. No profile in the shortlist that Pamela or her senior lead has not personally signed off on.
You lead. We orchestrate.
You interview finalists on your terms — technical assessment, systems design, take-home, panel, whatever your process needs. We schedule, gather feedback, and re-score internally. If a finalist drops out, we tap the sourcing bench, not the pool from scratch.
Signed contract, compliance handled
Offer negotiation, paperwork under the legal model you chose (contractor / EOR / AOR), compliance triple jurisdiction (IRS · 1099 · W-8BEN · PIPEDA · CASL · LFPDPPP). Start date locked. 90-day placement guarantee begins.
What STAR is, and why we use it
STAR — Situation, Task, Action, Result — is a structured behavioral interview framework that replaces the standard "tell me about yourself" chat with a protocol every interviewer can execute the same way. The candidate is asked to describe one specific past situation, the task they were assigned, the action they personally took, and the measurable result.
It works because it forces evidence. A candidate can claim they "led a migration to Kubernetes." STAR forces them to walk through which migration, what state the system was in, what they personally did versus their team, and how many hours of downtime the migration cost. Vague candidates fail this framework fast. Strong candidates give you data you can verify.
We pair STAR with a competency scorecard tailored to your role. Every STAR answer is scored 1-5 on the competencies that matter for the position, with the candidate's own words quoted as evidence. The scored scorecard travels with the candidate to your interviews so your team is not re-litigating what we already tested.
Example — STAR question for a senior backend engineer
"Walk me through a production incident you owned end-to-end in the last 12 months."
Which system, what state, how many users affected, when detected, how detected.
Ownership scope, urgency, stakeholders informed, business impact ceiling.
Not "the team did X" — what did YOU do, in what order, using what tooling, with what tradeoffs.
MTTR, users recovered, RCA published, follow-ups shipped, incidents prevented since.
Our AI agentic layer — amplify, not replace
The agentic layer is a set of AI agents that continuously scan our 25,000+ pre-screened candidate pool plus active market signals (public work, code contributions, open-role applications). When a new brief comes in, the agents rank preliminary matches against the competency scorecard, surface the top 30-50, and hand them to a human recruiter for STAR screening.
What the AI does: expand reach, do the boring pattern-matching, flag skill overlaps and gaps, translate signals from Spanish/Portuguese/English portfolios into a single scorecard. What the AI does not do: decide who reaches your shortlist. Every finalist has been interviewed and scored by a human before it ever touches your inbox.
This is why we call it AI-amplified, not AI-driven. The competitive frame — marketplace algorithm vs manual scouting — is a false binary. We built the third option.
Human curation — who signs off
Every shortlist is personally reviewed and approved by Pamela Herrera, Chief Talent Officer of NearTalent, or a senior of her team.
Pamela's background: 15+ years leading talent for transnationals across LatAm. Led TuHabi's talent function during its Series-C consolidation as a regional unicorn (100+ monthly hires at peak). Founder of the Mexican Series-C startup compensation club. She has personally interviewed thousands of senior candidates in tech, marketing, creative, data and operations.
What "signs off" means in practice: no candidate reaches your shortlist without Pamela or her senior lead reading the STAR interview notes, cross-checking the competency scoring, and validating the professional references. If she wouldn't hire this person into her own team, she won't send them to yours.
The 90-day placement guarantee
If a NearTalent placement does not work out in the first 90 days after start date — for any reason, on either side — we replace the hire at no additional search fee. We eat the cost of running the protocol again because we underwrite the shortlist we deliver.
Terms in plain English:
- Coverage window: 90 calendar days from the candidate's official start date.
- What triggers it: voluntary departure, involuntary separation, mutual decision to end. No fault-finding required.
- What we do: restart the protocol on the same role brief. New brief on day 1, agentic sourcing days 2-5, STAR screening days 5-8, shortlist by day 10.
- Payment: if you paid on placement, credit rolls into the replacement. If you paid on retainer, no additional invoice for the replacement search.
- Excluded: departures caused by material change in role scope, seniority or compensation from what was signed off on day 1 (we cannot underwrite a moving target).
Since 2016 we have exercised this guarantee on less than 6% of placements. The protocol is designed to catch fit gaps before they reach your team.
Ready to see the protocol in your inbox?
Brief today. Curated shortlist in 10 business days. Signed hire in 3 weeks. 90-day guarantee.
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