Data Labeling & RLHF

Human-Quality AI Training Data

High-volume, high-accuracy data operations for AI model training. RLHF annotation, content moderation, and QA — powered by our HumanInLoop platform.

iSuporta data operations team working on AI training data labeling
The Challenge

AI Models Need Better Data

Your AI model is only as good as the data it's trained on. Whether you're fine-tuning an LLM, building a classification model, or training a computer vision system — you need high-quality, human-labeled data at scale.

Crowdsourced platforms give you inconsistent quality. Building an in-house labeling team is expensive and slow to scale. You need reliable operators who understand annotation guidelines and deliver consistent results.

iSuporta provides trained data operators through our HumanInLoop platform. Our team handles RLHF annotation, text classification, image labeling, content moderation, and quality verification — all from our managed facility.

How We Solve It

Dedicated Team

Full-time professionals working exclusively for you from our Cebu facility.

AI-Augmented

Every team member is trained on modern AI tools relevant to their role.

US-Managed

US-based leadership ensures Western business standards and clear communication.

What We Do

Data Operations At Scale

RLHF annotation & ranking
Text classification & labeling
Image & video annotation
Named entity recognition (NER)
Sentiment analysis labeling
Content moderation
Data validation & cleaning
Document digitization & OCR QA
Quality assurance (inter-rater reliability)
Custom taxonomy & guideline development
AI Tools Our Team Uses
HumanInLoopScale AILabelboxExcel/MacrosCustom Annotation UIPython Scripts
Use Cases

Who This Works For

Real-world scenarios where our team delivers measurable results.

AI/ML

LLM Fine-Tuning

Our operators rank and evaluate LLM responses for RLHF training, providing the human feedback loop needed to align model outputs with user expectations.

Trust & Safety

Content Moderation

A team of trained moderators reviews flagged content for a social platform, handling edge cases that automated systems can't reliably classify.

Fintech

Document Processing

Operators verify OCR output, correct extraction errors, and validate structured data for a fintech company processing thousands of documents daily.

Transparent, All-Inclusive Pricing

One flat monthly rate per team member. Includes facility, equipment, HR, benefits, management, and AI tool training. No hidden fees.

Starting from$1,200/month per team member
FAQ

Common Questions

What is RLHF and how do you support it?
RLHF (Reinforcement Learning from Human Feedback) is a training technique where human operators evaluate and rank AI model outputs. Our operators follow your annotation guidelines to rate responses for quality, accuracy, helpfulness, and safety — providing the human feedback signal your model needs to improve.
How do you ensure labeling quality?
We use multi-pass review workflows, inter-annotator agreement metrics, and dedicated quality analysts. Every batch goes through a QA review before delivery. We target 95%+ accuracy on all labeling tasks.
Can you scale quickly?
Yes. We can ramp from a small pilot to 50+ operators within 2-3 weeks. Our facility infrastructure supports rapid scaling without quality degradation.
What annotation tools do you support?
We work with Scale AI, Labelbox, Label Studio, CVAT, and custom annotation interfaces. If you have a proprietary tool, we'll train our team on it.
How does HumanInLoop integrate?
HumanInLoop is our MCP-compatible execution platform. AI agents can route tasks directly to our operators via API. Results flow back automatically. It's designed for AI-in-the-loop workflows where human judgment is needed at specific steps.
What languages do your operators support?
Our Cebu team primarily supports English. For other languages, we can recruit specialized operators. Filipino operators have native-level English proficiency.
Get Started

Need Human Operators for AI Training?

Whether you're training models, moderating content, or labeling data — we have the trained workforce ready.