Where GenAI meets
the real world.
Multilingual data, evaluation, and annotation, grounded in domain expertise and native language understanding.
The verticals driving
the next wave of AI investment.
Vision · Spatial · Motion
Reasoning · Tool Use · Eval
Autonomous Vehicles
Perception · LIDAR · Edge
Voice AI &
Speech
Speech
ASR · TTS · 155+ Locales
Foundation Model Alignment
RLHF · Safety · Preference
Multimodal & Generative AI
Image · Video · Cross-modal
Recognition
2026
Winner
Fraud Detection and Prevention
2026
Winner
Best Cyber Security Innovation
2026
Finalist
Best Use of Data
2025
Shortlisted
Best Use of AI in Cybersecurity
The full stack of
human intelligence
for AI development.
01
AI Training Data
Data Collection02
Human-in-the-Loop Evaluation
Model Evaluation03
RLHF & Preference Data
Alignment05
Safety & Red-teaming
AI Safety06
Custom Benchmark Design
BenchmarkingGeneric contributors
produce generic results.
Your model deserves better.
Crowdsource platforms give you volume. They don’t give you domain expertise, cultural grounding, or the governance infrastructure that enterprise AI teams require. That’s the gap Welo Data was built to close.
Contributor quality, not just quantity
Welo Data’s rigorous qualification process ensures every contributor is domain-matched, not randomly assigned to tasks outside their expertise.
130+ behavioral variables. 1M+ events monthly. NIMO blocks fraudulent applicants, detects quality drift in real time, and provides the audit trail your governance team needs.
Enterprise compliance built in
7 ISO certifications, SOC 2, GDPR, HIPAA. 14+ secure facilities. Governance teams can show exactly how their training data was produced, by whom, and under what controls.
Not a platform. A partner.
Welo Data is not a self-serve marketplace. Every program is scoped, staffed, and monitored by our team, with a dedicated point of contact from kickoff through delivery.
From scope to
production-ready
data and evaluation.
01
Scope & Design
We align on use case, languages, domains, quality thresholds, and deliverable format with your team before a single task is assigned.
02
Contributor Matching
Domain experts and native speakers are selected from our 500K+ vetted workforce. Every contributor is matched to the task, not randomly assigned.
03
Multi-layer QA with NIMO monitoring every session in real time. Inter-annotator agreement tracked continuously. Quality scores above 90% maintained throughout.
04
Delivery & Iteration
Structured data in your preferred format. Accuracy improves +10% per iteration. Ongoing support as your model evolves, with full auditability at every stage.
Every AI use case.
One trusted partner.
Instruction tuning & SFT data
High-quality prompt-response pairs written by domain experts, not scraped or synthetically generated without human validation.
Named entity recognition & classification
Precise labeling across legal, medical, financial, and technical domains. Consistency enforced by NIMO across every annotation session.
Summarization & generation evaluation
Human judges assess relevance, factuality, coherence, and tone, structured rubrics designed around your model’s specific risk profile.
Multilingual NLP across 155+ locales
Not just translation, cultural grounding, dialect coverage, and native fluency. Gaps that automated approaches cannot close.
Audio & Voice AI
Voice data that reflects how real people talk, not how scripts were read.
Get in TouchSpeech transcription & diarization
Native-speaker transcribers across 100+ languages, including low-resource dialects rarely covered by automated ASR systems.
Audio data collection for Voice AI
Scripted and spontaneous recordings from diverse speaker populations. Controlled acoustic variation for robust ASR and Voice AI training.
Emotion & sentiment labeling
Affective annotation by trained raters who understand cultural norms around emotional expression, not crowdsource approximation.
TTS & voice model evaluation
Expert phoneticians and language specialists assess TTS output and speech model performance against native-speaker standards across 155+ locales.
Vision & Multimodal
Image, video, and cross-modal annotation for robotics, AV, and beyond.
Get in TouchObject detection & segmentation
Precise bounding boxes, polygons, and semantic masks, validated by multi-annotator consensus and NIMO quality monitoring.
AV & robotics perception data
LIDAR point cloud annotation, sensor fusion labeling, and spatial scene understanding for autonomous vehicle and robotics programs.
Video temporal annotation
Frame-level and clip-level annotation for action recognition, activity detection, and video understanding at scale.
Image-text alignment evaluation
Human judges assess whether captions and model descriptions accurately reflect image content, critical for multimodal model evaluation.
RLHF & Alignment
Preference data that reflects real human values, not averaged crowd opinion.
Get in TouchPairwise preference ranking
Side-by-side comparison tasks designed to elicit genuine preference, not anchoring bias or positional effects that contaminate crowdsource RLHF.
Constitutional AI evaluation
Structured rubrics for harmlessness, honesty, and helpfulness, applied by trained raters who understand the distinction, not checkbox workers.
Safety & red-teaming
Adversarial probing to surface failure modes before deployment. Documented methodology that satisfies enterprise AI governance requirements.
Iterative fine-tuning support
Continuous evaluation loops that improve model accuracy +10% per iteration. Welo Data supports the full RLHF cycle, not just the first pass.
Agentic & Reasoning
Evaluation infrastructure for agentic AI, where automated metrics fall short.
Get in TouchMulti-step task evaluation
Human judges assess agentic task completion, not just final output, but the quality of intermediate reasoning steps that automated metrics miss.
Tool use & function call validation
Expert evaluators assess whether agents select and use tools correctly, across domains from code execution to web browsing to API calls.
Chain-of-thought & reasoning traces
Structured evaluation of reasoning quality, logical coherence, step validity, and alignment between stated reasoning and final outputs.
Custom benchmark design
Evaluation frameworks built for your model’s specific domain and deployment context, not adapted from generic public benchmarks.
Proven in production.
View all case studiesMultilingual QA
Scaling QA across three global regions without losing fidelity
Major global technology company, 99%+ on-time delivery, 4.9/5 quality scores, <1% rejection rate
Read case studyAI Benchmarking
Building reliable coding benchmarks for data science agents
Fortune 100 cloud technology company, expert-validated benchmark suite across data science domains
Read case studyMachine Translation
Multilingual precision at scale: machine translation post-editing
Fortune 500 global e-commerce company, multilingual MTPE across production-scale content pipelines
Read case study“The quality bar Welo Data holds their contributors to is genuinely different. We’ve worked with other annotation vendors. The difference isn’t marginal, it’s the reason our model performs the way it does in production.”
Head of AI, Enterprise Software Company
What enterprise buyers
actually ask us.
Ready to scope a program?
Get answers specific to your use case.
Tell us your use case, languages, and quality requirements, our team will come back with a clear picture of scope, timeline, and what delivery looks like.
Are you a crowdsource platform?
No. Welo Data is a managed services partner, not a self-serve marketplace. Every program is scoped, staffed with domain-matched contributors, and monitored by our team using NIMO, our proprietary quality system. You work with a dedicated program team, not a platform dashboard.
How quickly can a program launch?
Timeline depends on task complexity, language coverage, and domain specificity, all of which we assess in the scoping conversation. Our team moves quickly once requirements are clear, and contributor matching typically happens in parallel with finalizing task design.
How do you ensure data quality at scale?
NIMO monitors 130+ behavioral variables across every annotation session, not just final outputs. Inter-annotator agreement is tracked continuously. Fraudulent contributors are blocked before they touch your data. Quality scores are consistently above 90%, with accuracy improving +10% per iteration.
What compliance and security standards do you meet?
7 ISO certifications, SOC 2, GDPR, and HIPAA compliance. 14+ secure facilities globally. Full audit trails on contributor identity, task assignment, and quality monitoring, so your governance team can answer how your training data was produced, by whom, and under what controls.
Do you work with low-resource languages?
Yes. 155+ locales including dialects and regional variants that most annotation vendors simply don’t cover. Our 25+ years of language services work means we have established contributor networks in markets where others have to start from scratch.
What makes Welo Data different from other annotation vendors?
Three things competitors can’t replicate: NIMO (our proprietary quality monitoring system, not a checklist layer); 25+ years of language services DNA from our Welocalize parent (actual multilingual infrastructure, not a translation API); and a rigorous contributor qualification process that produces domain-matched specialists, not a generic crowd.
Build AI that holds up
beyond the lab.
Tell us your use case, languages, and quality requirements, we’ll come back with a clear picture of what delivery looks like.
