AI Training Data, Annotation, and Evaluation Services for Enterprise AI Teams
Genmorphics delivers RLHF data, SFT datasets, multimodal annotation, and model evaluation through 20,000+ domain-vetted experts across 40+ languages. You bring the data and requirements. We handle annotation, validation, QA, and delivery.
20,000+
Verified Experts
50+
Projects Delivered
98%+
Quality Score
36+
Countries Covered
Industries We Serve
What We Do
End-to-End AI Data Services
You provide the data and requirements. We handle annotation, validation, review, and quality control through domain-vetted experts and managed QA workflows.
LLM Training Data
Our experts write, rank, and evaluate RLHF, SFT, and prompt-response datasets. Real domain knowledge in every preference label, instruction pair, and model evaluation.
Agentic AI & Tool Use
Our annotators evaluate function calls, trace reasoning chains, and find failure points in agent workflows. This is the human feedback loop agentic AI systems need.
Multimodal Annotation
We annotate image, video, audio, OCR, and multimodal datasets with bounding boxes, segmentation, keypoints, video tracking, transcription, and structured labels.
Domain-Expert Labeling
Your data is reviewed by domain-matched professionals across healthcare, legal, engineering, STEM, finance, code, safety, and multilingual workflows.
AI Safety & Evaluation
Our evaluators stress-test models for jailbreaks, bias, hallucinations, factuality issues, unsafe responses, and policy violations before deployment.
Multilingual Data
Native-language experts across 40+ languages annotate, translate, localize, and validate data with the cultural context global AI products require.
Our Process
From Sample Data to Production Delivery
A clear five-step process from share to deliver, built for the speed and quality enterprise AI teams expect.
Share Requirements
Tell us about your dataset, annotation goals, quality standards, timeline, and delivery format.
- Dataset type and volume
- Quality targets
- Timeline and format
Scope & Pilot
We review your requirements, recommend the right workflow, and complete a pilot batch to align quality expectations.
- Workflow recommendation
- Representative pilot batch
- Quality alignment
Build Guidelines
We create or refine annotation guidelines, label definitions, examples, edge cases, and acceptance criteria.
- Label taxonomy
- Edge-case handling
- Acceptance criteria
Scale Production
A trained team completes annotation with reviewer oversight, QA checks, and project management support.
- Trained annotation team
- Reviewer oversight
- Progress tracking
Deliver & Improve
You receive versioned output with QA notes, correction handling, and feedback-based iteration.
- Versioned dataset delivery
- QA notes and corrections
- Feedback-driven iteration
Domain-Matched Teams
Experts assigned by use case, language, and quality history
Pilot-First Approach
Validate guidelines and quality on a small batch before scaling
Multi-Level QA
Reviewer checks, expert audits, and inter-annotator agreement tracking
Transparent Delivery
Milestone-based handoff with versioned output and clear acceptance criteria
Free scoping call. No commitment required.
Why Genmorphics
Built for Enterprise AI Data Needs
Annotation, validation, and evaluation built to enterprise standards: vetted experts, measured quality, secure delivery, and a pilot-first approach to scale.
Domain-Vetted Experts
Every annotator is screened by a domain lead before joining a project. Clinicians on medical work. Lawyers on legal. Engineers on code. No crowd workers on specialist tasks.
Managed QA at Scale
Multi-level review, inter-annotator agreement tracking, and reviewer adjudication built into the workflow. We measure quality per project and report it alongside delivery.
Data Security First
NDA per annotator, role-based access, support for client-controlled environments, and audit trails on every annotation action. We follow your security model, not the other way around.
Pilot-to-Production Path
Start with a 3 to 5 day pilot batch. We validate guidelines, calibrate the team, and stress-test tooling before scaling. Production only begins when both sides agree on what good looks like.
Our Trainers
Our Expert Team
Every expert is verified through our AI assessment. Here are a few of the professionals who deliver quality on client projects.
Nuzhat
Multimodal QA Lead
Shafew
Data Extraction Expert
Peyal
Bounding Box QA
Saaquib
Edge Case QA Reviewer
Elena Volkov
Multilingual Content Expert
Dr. Kenji Tanaka
AI Safety Evaluator
For Domain Experts
Active Project Categories
Open work for verified experts across the domains our clients need most.
Testimonials
What Clients Say
Feedback from AI teams using Genmorphics for annotation, evaluation, validation, and quality-controlled data delivery.
David P.
Head of AI, Series B AI Startup
“Two annotation vendors burned us before Genmorphics. Nafis's team was the first group that actually understood what RLHF data needs to look like. 50K annotations at 98% agreement. Did not think we could hit that on the timeline we had.”
Maria S.
VP of Engineering, Healthcare AI Company
“Nuzhat ran QA across a 100-person annotation team on our multimodal medical dataset. Inter-annotator agreement stayed above 90% the entire ramp. After retraining on her team's labels, our model error rate dropped 34%. We stopped second-guessing the annotations.”
Thomas W.
CTO, Legal Tech Startup
“Shafew handled PDF data extraction across our entire contract corpus. Entity extraction hit 96.7%. He flagged edge cases our in-house lawyers had missed and walked us through why specific extractions were tricky instead of only sending numbers.”
FAQ
Common Questions
Things people usually ask before getting started.
AI training data annotation is the process of adding structured labels, ratings, or human feedback to raw datasets so machine learning models can learn from them. It includes labeling images and video, writing or ranking text responses for LLMs, transcribing audio, extracting structured data from documents, and evaluating model outputs for accuracy, safety, and policy adherence.
Ready to Build Better Training Data?
Send us your sample task or project requirements. We'll recommend the right workflow, expert team, timeline, and pricing model.
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