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RLHF · Red Teaming · Agentic Eval · Multimodal

Expert human intelligence
for AI that performs.

Your model is only as good as the humans who trained it. We staff the specialists who train, judge, and red-team frontier AI — across RLHF, safety, multimodal eval, and 50+ languages.

Domain RLHFAgentic EvalFactuality & Grounding
Built for
Vertical AI companiesAI-native startupsFortune 500 AI teamsMajor systems integrators
Design Partners Program — Wave 1 (2026)

Building with a limited cohort of inaugural partners this year.

Partners co-shape our rubrics, pricing, and SLAs — and get preferred access to our senior Architects and Adversaries. We're looking for Vertical AI companies, AI-native startups, and enterprise AI teams running a production RLHF, red-team, or factuality program in 2026.

Apply for Wave 1 →
Why specialization matters

The next generation of AI demands
a different kind of human expertise.

As AI models mature and move into healthcare, legal, finance, security, and enterprise operations, the quality of human input becomes the defining variable. More data is no longer enough. The right expertise — deeply embedded in your program — is what separates models that perform from models that fail in production.

Expert-in-the-Loop (EITL)
Beyond human-in-the-loop.

General annotators produce general quality. Credentialed domain experts produce production-grade AI. Every engagement is built around the right specialist — Architects who set the standard, Judges who enforce it, Adversaries who stress-test it — matched to the depth your model actually needs.

Credentialed ExpertsDomain JudgesNamed Specialists
Domain Specialization
Every domain needs its own expert.

A clinical expert evaluating clinical RLHF pairs catches failure modes a general annotator never sees. A legal specialist red-teaming a legal AI finds liability traps that prompt engineers miss. A safety-certified researcher identifies dangerous knowledge refusals that only a domain specialist recognizes. The credential is not a credential — it is the capability itself.

Credentialed Domain ExpertsRLHF · Red Teaming · Safety
🔒
Sovereign Delivery
Your data stays in your environment.

For frontier AI labs, regulated enterprises, and government programs, the training data, model outputs, and proprietary prompts used in evaluation are among the most sensitive IP a company holds. We build every engagement with data sovereignty as the foundation — on-premise deployment, secure facilities, air-gapped options, and zero third-party data access. Not an exception. The default. Built for programs where data residency is non-negotiable.

On-Premise DeliverySecure FacilitiesData SovereigntyAir-Gapped Ready
Embedded Collaboration
Inside your team, not at arm's length.

The most effective RLHF, evaluation, and annotation programs are not vendor-to-client. They are team-to-team. Our specialists embed directly into your workflows, tools, and quality framework — building the institutional knowledge that makes feedback more consistent and more valuable over time. A standing capability, not a periodic deliverable.

Embedded TeamsLong-Term ProgramsInstitutional Knowledge

What a Quantryx engagement
actually looks like.

Every program begins with a 6-week Calibration POD, then scales into steady-state delivery. Five moments where our work shows up in your model.

Week 1-2
Your eval rubric goes from debatable to kappa-stable.
CalibrationGold DatasetKappa BaselineRubric Co-Design
Week 3-6
The first RLHF pass lands — preferences ranked by credentialed judges, not crowd workers.
RLHFSFT / CoTPreference TrainingDPO
Week 4-8
Adversaries break the model before your users do.
Red TeamingJailbreak TestingDomain Safety Audit
Ongoing
Factuality audits catch hallucinations with source citations and reproduction steps.
RAG GroundingCitation VerificationHallucination Forensics
Ongoing
The model ships in every language your users speak — native, not translated.
Native RLHFCultural AdaptationLocalization Judge50+ Languages
AI / ML Practice

Five service pillars aligned
to enterprise AI programs.

Built around how global technology companies organize human intelligence operations — covering the full AI development and operations lifecycle across all five program categories.

Pillar 01
AI Data & Training

The human input that trains, evaluates, and aligns foundation models — from raw data labeling to expert-level RLHF and adversarial red teaming.

Workflows: Data Annotation & Labeling · Model Validation & Evaluation · Data Collection & Sourcing
RLHFSFT / CoTMultimodalRed Teaming
Pillar 02
Content Loop

The quality and safety layer keeping AI-generated and user-generated content accurate, policy-compliant, and culturally appropriate globally.

Workflows: Content Creation & Curation · Content Moderation · Localization & Translation
Content ModerationTrust & Safety50+ Languages
Pillar 03
User Feedback

Human-in-the-loop analysis of how real users respond to AI products — high-volume feedback triage to nuanced sentiment and structured user research.

Workflows: Feedback Triage · Human-in-Loop Sentiment Analysis · User Research Support
Feedback TriageSentiment AnalysisUser Research
Pillar 04
Search Content Operations

The human intelligence behind accurate, trustworthy search and knowledge graph data — covering ingestion, QA, and content strategy for AI-powered search at global scale.

Workflows: Content Acquisition & Ingestion · Content Curation & QA · Content Understanding & Strategy
Search QualityKnowledge GraphTaxonomy
Pillar 05
Enablement & Governance

Strategic advisory, managed service programs, and analytics that build the frameworks, policies, and reporting infrastructure keeping AI operations accountable.

Workflows: Consulting & Advisory · Managed Service Providers (MSPs) · Analytics & Reporting
AI PolicyGovernanceMSPGDPR / CCPA
Each pillar is staffed with specialists in specific technical capabilities.
Technical Capabilities
RLHF
Reinforcement Learning from Human Feedback

Human evaluators rank and rate model outputs, teaching the reward model what good looks like. Results in models that are more helpful, coherent, and aligned with real user intent across text, code, and reasoning.

Preference RankingReward ModelingDPO
SFT / CoT
Supervised Fine-Tuning & Chain-of-Thought

Human-written demonstrations establish baseline model behavior. CoT training teaches structured, step-by-step reasoning for complex tasks. The foundation every well-aligned model is built on — before RLHF begins.

Instruction TuningReasoning DemosSFT Data
Multimodal Evaluation
Text, Image, Audio & Video Model Evaluation

Expert evaluators for vision-language models, audio understanding, and multimodal reasoning. Performance tested against real-world tasks, not benchmark datasets. Coverage scales with your model's modality footprint.

VLM EvalASR / TTSVideo QA
Audio AI & Voice
Voice Intelligence & Native Language Evaluation

Native speaker annotators for ASR, TTS, and conversational AI. Multilingual evaluation with cultural adaptation — not translation. Covers 50+ languages.

ASRTTSLocalization Eval50+ Languages
Data Annotation
Expert Annotation Across All Data Types

Annotators for text, image, audio, video, LiDAR, and structured data. Domain specialists for medicine, law, finance, coding, and science — where general annotators produce incorrect labels. Every label traceable.

ImageAudioVideoLiDARNLP
Red Teaming & Safety
Adversarial Testing Before Production

Systematic adversarial testing by domain specialists. Jailbreaks, bias, harmful outputs, and safety violations across text, code, and multimodal systems. Structured findings with reproduction steps and recommended fixes.

Jailbreak TestingBias DetectionSafety Eval
Factuality & Grounding Audit
RAG Grounding Verification

Specialists verify model outputs against source documents, trace citations, and flag hallucinations with reproduction steps. Built for AI products where a wrong answer carries real-world consequence.

RAG GroundingCitation VerificationHallucination Forensics
AI Risk & Compliance Evaluation
Regulatory-Grade Model Assessment

Model risk review, bias audits, and compliance documentation that stands up to enterprise procurement and regulatory inquiry. Built for AI products entering regulated markets.

Model RiskBias AuditCompliance Documentation
Knowledge Graph & Ontology
Domain Graph Architecture

Specialists and ontologists who design entity models, taxonomies, and relationship schemas for domain-specific AI. For products where meaning and context matter more than surface text.

Ontology DesignEntity ResolutionTaxonomy Engineering
Agent & Model Evaluation
End-to-End Agent & Model Quality

Response quality scoring, safety evaluation, cultural adaptation analysis, and headroom analysis for AI agents and foundation models. Side-by-side evaluation, localization testing, and production drift detection. Includes agentic reasoning evaluation — multi-step tool use, planning trajectories, and end-to-end workflow quality.

SxS EvalSafety ScoringDrift DetectionAgentic Eval
Content Ops & Search Quality
Content Operations, Trust & Safety, Search

Content quality reviewers, trust and safety specialists, and search quality raters who keep AI-powered products accurate and policy-compliant at scale. Ongoing operations programs that scale with your product.

Content ModerationSearch RelevanceTrust & Safety
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Language Capability

50+ languages.
Cultural intelligence,
not just translation.

A model that performs in English can fail in Japanese or Arabic — not from grammar errors, but from cultural context, regional sensitivity, and domain nuance that automated translation misses. We provide native-speaker specialists who understand the culture, not just the language.

Native Language RLHF
Preference ranking and SFT authored in the target language by native speakers — not translated from English.
Cultural Adaptation
Audit for regional sensitivities, dialect appropriateness, and cultural common-sense consistency.
Localization Judge
Expert review of model outputs for cultural accuracy, idiom usage, and locale-appropriate tone.
ASR / TTS Evaluation
Audio AI evaluation by native speakers with i18n rubrics adapted per locale — not per language family.
✓ Active language coverage
Americas
English · Spanish (ES / LA)
Portuguese (BR / PT)
French (CA)
Europe
French · German · Italian
Dutch · Polish · Czech
Turkish · Swedish
Middle East & Africa
Arabic (MSA / Gulf / Levant)
Hebrew · Farsi
Swahili · Yoruba · Amharic
Asia Pacific
Japanese · Korean
Mandarin (CN / TW) · Hindi
Thai · Vietnamese · Tagalog
Indonesian · Bengali
Don't see your language?
We source native speakers for additional languages on request. Let us know your locale requirements.
POD-Based Delivery

Three POD types.
Built for long-term programs.

Every POD is named, credentialed, and built for continuity — no rotating crowd workers, no ticket-defined scope, no surprise handoffs.

01 — Calibration POD
4-6 specialists · Architects + Judges

Phase one of every program. Builds the evaluation rubric, gold dataset, calibration set, and kappa baseline with your team. The foundation the ongoing program runs on top of.

02 — Production POD
5-12 specialists · Judges + Adversaries + PM

Steady-state operations. RLHF, red-teaming, factuality audit, content ops, drift monitoring. Includes embedded program management, QA, and calibration. Scales with your program.

03 — Advisory POD
1-2 specialists · Senior Architects

Embedded strategic capacity for AI governance, eval framework design, regulatory readiness, and RFP response. Retainer model with direct access to domain leadership.

Cognitive Role Framework — three specialist types, tiered by depth
Tier 1 — Expert
Architects

Build the ground truth. Design evaluation rubrics, author SFT/CoT training data, establish the gold standard. High-stakes, high-judgment work.

Reasoning Experts (Math / Physics / Bio) · Code Architects · AI Tutors · Multimodal Annotators · Agentic Reasoning Architects · Knowledge Graph Specialists
Credentialed Domain Experts
Tier 2 — Specialist
Judges

Evaluate against the standard. RLHF preference ranking, hallucination forensics, competitive evaluation, inference quality review. The expanded middle of every program.

Competitive Eval Leads · Preference Rankers · Hallucination Specialists · Localization Judges · Inference Auditors · Factuality & Grounding Auditors · AI Risk & Compliance Evaluators
Masters / Domain Experts
Tier 1 — Expert
Adversaries

Break the model before users do. Adversarial testing, red teaming, domain safety auditing — credentialed specialists only.

Adversarial Engineering · Financial Adversaries · Domain Safety Auditors
Credentialed Domain Experts
About Quantryx

Expert human judgment
is irreplaceable in AI.

Quantryx was built on a clear conviction: the quality of an AI system is ultimately determined by the quality of human input it receives. Better RLHF data produces better-aligned models. More rigorous red teaming produces safer systems. More expert annotation produces more capable models.

We are an AI services company based in the Bay Area. We work across five AI service pillars — providing the Cognitive Role Framework and the accountability that production AI requires. Embedded in your team, not operating at arm's length.

We bring operational discipline and domain expertise to every engagement — from frontier AI programs to production AI deployments in regulated enterprises.

Our engagement portfolio spans AI-native companies, frontier AI research organizations, Fortune 500 technology teams, regulated enterprises, and major systems integrators.
Domain expertise, not generalist labor.

Our Cognitive Role Framework places the right specialist — Architect, Judge, or Adversary — at the right tier. Every task matched to the credential and depth it actually requires.

Diamond model delivery.

AI-augmented Tier 3 practitioners handle volume. Tier 1 and Tier 2 specialists focus on the high-judgment tasks that determine model quality. More output, right expertise at every level.

Outcome-defined, not headcount-defined.

Every engagement is scoped around what the client achieves. Quality targets and program outcomes are defined before work begins — not renegotiated after problems surface.

Built for long-term programs.

Continuity produces quality. Our specialists stay — and so do we. We remain engaged for the life of the program, ensuring consistency as the work evolves and scales.

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