BQ: The expert network Primary AI labs actually need.
- Nexus is a B2B market research company delivering rigorous primary and secondary market research across 30+ countries. Our team of B2B market research specialists combines qualitative depth, quantitative scale, and competitive intelligence to support strategic decisions.
Nexus AI Expert Network
- An AI expert network connects AI labs and healthtech companies with credentialed domain specialists, including physicians, engineers, and industry veterans, for training data, model evaluation, and clinical or technical validation. Unlike generalist annotation platforms, Nexus custom-recruits every expert to your project's exact credential and regulatory requirements, rather than matching from a fixed talent pool. This distinction matters most when your submission will face regulatory scrutiny, when a generalist annotator's error could invalidate months of training data, or when the specialist you need was never going to apply to a crowdsourced platform in the first place.
Portfolio Lifecycle Strategy
What We Actually Deliver
- Nexus operates across four core service areas, each requiring a different credential profile and a different kind of sourcing discipline.
Domain Expert Recruitment for AI Training
Board-certified specialists, including radiologists, sonographers, engineers, and aviation technical leads, recruited for supervised fine-tuning, prompt-response authoring, and domain-grounded training data generation. The credential bar is set by your project requirements, not by what happens to be available in a pre-built pool.
Clinical and Technical Validation
Second-line expert reviewers who validate annotations for regulatory-grade accuracy. Built for submissions where regulators will request CVs and documented qualifications for every reader. Every screened candidate meets that bar before a profile reaches your team.
Model Evaluation and Red-Teaming
Structured expert review of model outputs against domain-specific rubrics. A consultant radiologist reviewing a diagnostic AI output will catch errors a generalist evaluator would never flag, because the error only looks like an error if you know what correct actually looks like.
RLHF and Preference Ranking
Domain experts ranking model responses by real-world correctness, not just fluency. When your reward model learns from people who would actually know whether an answer is right, the signal quality is categorically different from crowdsourced preference data.
Real Work, Not Hypotheticals
- The projects below represent the kind of work Nexus actually delivers. Each one required a specialist who could not have been sourced from a general-purpose annotation platform or a talent marketplace.
Pediatric Radiograph Annotation for a Diagnostic AI Company
Recruiting consultant radiologists with documented pediatric sub-specialty training to perform ground-truth annotation ahead of FDA and CE regulatory submission. The credential requirement was explicit: every reader's qualifications needed to survive regulator scrutiny, not just pass an internal competency check. Nexus sourced and screened candidates against that bar from the outset.
Clinical Validation for a Prenatal Ultrasound AI Platform
Sourcing sonographers, radiologists, and OB/GYN specialists to validate AI-generated ultrasound annotations against clinical guidelines. This was an ongoing production pipeline, not a one-off project, which meant building a validated cohort capable of scaling with the client's release cadence rather than delivering a single batch of profiles.
Technical Records Experts for an Aviation Maintenance AI Tool
Recruiting aviation technical records managers and maintenance planners across Tier 1 and regional airlines to red-team AI outputs on real-world lease-return and maintenance-preparation scenarios. The expertise required was narrow enough that no platform had a ready pool. Nexus sourced directly.
Enterprise Architecture Review for a Knowledge-Fabric AI Platform
Sourcing Chief Architects and Distinguished Engineers with 20-plus years of enterprise platform experience to evaluate whether a new AI architecture pattern holds up against real enterprise operating models. The client needed people who had actually built and operated infrastructure at that scale, not practitioners with adjacent credentials.
- The pattern across allfour: the specialist required was too credentialed, too specific, or too senior to have joined a talent marketplace. Custom outreach was the only viable path.
Why Custom Recruitment, Not a Talent Marketplace
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Automated vetting platforms work when thousands of people are competing to get in. Most hard AI problems are not like that.
The Chief Radiologist with documented pediatric sub-specialty experience and a clean regulatory record was never going to apply to a crowdsourced annotation pool. The Distinguished Engineer who has actually run enterprise infrastructure at scale is not browsing a talent marketplace. These people exist, but they are not findable through a self-serve search. They have to be found, approached directly, and given a compelling reason to engage.
That is what Nexus does.
Three things that make this different from every other option
Recruited from scratch for every project.
Not matched from a static database. Every engagement starts with custom outreach targeted at the specific credential profile, geography, and sub-specialty your project requires.
Documentation built for regulators, not just internal QA.
When a client says "regulators will request CVs and qualifications for every reader," that is the standard Nexus screens to from day one, not a requirement added after the first submission gets questioned.
A relationship, not a self-serve dashboard.
Every engagement starts with a scoping call, a custom screener, and a named point of contact. There is no algorithm deciding who is a close enough match. There is a person accountable for getting it right.
- The practical consequence: when your project has a narrow credential requirement, a regulatory deadline, or a specialist profile that does not exist in any pre-built pool, Nexus is the path that works. Marketplace platforms are built for volume and breadth. Nexus is built for precision.
How It Works
- Every engagement follows the same five-step process, designed to move from scoping to delivered profiles in 48 hours.
Engagement 1
Scope the project
- A short call to define the domain, the credential bar, any regulatory or compliance requirements, and the timeline. This is where Nexus establishes exactly who is needed, not an approximation.
Engagement 2
Recruit, not match.
- Custom outreach to the specific specialists who fit the brief. Not a search through a static pool, not an algorithm surfacing whoever is currently available.
Engagement 3
Screen and verify credentials.
- Every candidate is checked against your stated requirements before a profile reaches your inbox. Credential documentation is prepared to the standard the engagement requires.
Engagement 4
Deliver in 48 hours.
- Profiles land ready for review or onboarding. For regulatory submissions, supporting documentation is included.
Engagement 5
Scale with ongoing support.
- For validator cohorts and production pipelines, Nexus continues sourcing as your project grows. The relationship does not end at first delivery.
- Typical timeline: scoping call to first profiles in 48 hours. For large cohorts or complex regulatory requirements, a delivery schedule is agreed at scoping.
Transparent Pricing, No Subscription
- Every other major expert network requires a sales call to learn pricing. We don't.